Contributors: Epidémiologie et Analyse des Maladies Infectieuses - Infectious Disease Epidemiology and Analytics; Institut Pasteur Paris (IP)-Université Paris Cité (UPCité); Tallaght Hospital; Trinity College Dublin; Virus et Immunité - Virus and immunity (CNRS-UMR3569); Institut Pasteur Paris (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité); Centre Hospitalier Regional d'Orléans (CHRO); Centre Hospitalier Universitaire Strasbourg (CHU Strasbourg); Hôpitaux Universitaires de Strasbourg (HUS); Institut National de la Santé et de la Recherche Médicale (INSERM); Immuno-Rhumatologie Moléculaire (IRM); Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM); This work was supported by the Fondation pour la Recherche Médicale (CorPopImm to MW), the French Government’s Laboratoire d’Excellence “Integrative Biology of Emerging Infectious Diseases” (Investissement d’Avenir grant n°ANR-10-LABX-62-IBEID), and INCEPTION programs (Investissement d’Avenir grant ANR-16-CONV-0005). SFK’s laboratory is funded by Strasbourg University Hospitals (SeroCoV-HUS; PRI 7782), the Agence Nationale de la Recherche (ANR-18-CE17–0028), Laboratoire d’Excellence TRANSPLANTEX (ANR-11-LABX-0070_TRANSPLANTEX) and Institut National de la Santé et de la Recherche Médicale (UMR_S 1109). The NH-COVAIR Study was funded by a grant from the Meath Foundation, Tallaght University Hospital. A.H.D. has been awarded the Irish Clinical Academic Training (ICAT) Programme, supported by the Wellcome Trust and the Health Research Board (Grant Number 203930/B/16/Z), the Health Service Executive, National Doctors Training and Planning, and the Health and Social Care, Research and Development Division, Northern Ireland. N.B. is funded under the Science Foundation Ireland Phase 2 COVID-19 Rapid Response Call (20/COV/8487) and the Health Research Board COVID-19 Rapid Response Call (COV19e2020e053).; The authors are grateful to healthcare workers and nursing home residents who participated in this study.; ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010); ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016); ANR-11-LABX-0070,TRANSPLANTEX,Nouveaux loci d'histocompatibilité/biomarqueurs en transplantation humaine: de la découverte à l'app(2011)
Abstract: International audience ; Serological assays capable of measuring antibody responses induced by previous infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been critical tools in the response to the COVID-19 pandemic. In this study, we use bead-based multiplex assays to measure IgG and IgA antibodies and IgG avidity to five SARS-CoV-2 antigens (Spike (S), receptor-binding domain (RBD), Nucleocapsid (N), S subunit 2, and Membrane-Envelope fusion (ME)). These assays were performed in several cohorts of healthcare workers and nursing home residents, who were followed for up to eleven months after SARS-CoV-2 infection or up to six months after vaccination. Our results show distinct kinetic patterns of antibody quantity (IgG and IgA) and avidity. While IgG and IgA antibody levels waned over time, with IgA antibody levels waning more rapidly, avidity increased with time after infection or vaccination. These contrasting kinetic patterns allow for the estimation of time since previous SARS-CoV-2 infection. Including avidity measurements in addition to antibody levels in a classification algorithm for estimating time since infection led to a substantial improvement in accuracy, from 62% to 78%. The inclusion of antibody avidity in panels of serological assays can yield valuable information for improving serosurveillance during SARS-CoV-2 epidemics.
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