Kinetics of the Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Response and Serological Estimation of Time Since Infection

Stéphane Pelleau (1, 2) , Tom Woudenberg (1, 2) , Jason Rosado (1, 2, 3) , Françoise Donnadieu (1, 2) , Laura Garcia (1, 2) , Thomas Obadia (1, 2, 4) , Soazic Gardais (2) , Yasmine Elgharbawy (2) , Aurelie Velay (5, 6) , Maria Gonzalez (6) , Jacques Yves Nizou (7) , Nizar Khelil (7) , Konstantinos Zannis (7) , Charlotte Cockram (8) , Sarah Hélène Merkling (9) , Annalisa Meola (10) , Solen Kerneis (11, 12) , Benjamin Terrier (13, 14) , Jerome de Seze (15) , Delphine Planas (16) , Olivier Schwartz (16) , François Dejardin (17) , Stéphane Petres (17) , Cassandre von Platen (18) , Sandrine Fernandes Pellerin (18) , Laurence Arowas (19) , Louise Perrin de Facci (19) , Darragh Duffy (20) , Clíona Ní Cheallaigh (21, 22) , Jean Dunne (21, 22) , Niall Conlon (21, 22) , Liam Townsend (21, 22) , Veasna Duong (23) , Heidi Auerswald (23) , Laurie Pinaud (24) , Laura Tondeur (24) , Marija Backovic (10) , Bruno Hoen (25) , Arnaud Fontanet (24, 26) , Ivo Mueller (2, 27, 28) , Samira Fafi-Kremer (5) , Timothée Bruel (16, 29) , Michael White (1, 2)

1 Epidémiologie et Analyse des Maladies Infectieuses - Infectious Disease Epidemiology and Analytics
2 Malaria : parasites et hôtes - Malaria : parasites and hosts
3 ED 393 - Santé publique : épidémiologie & sciences de l'information biomédicale
4 Département de Biologie Computationnelle - Department of Computational Biology
5 Immuno-Rhumatologie Moléculaire
6 CHU Strasbourg
7 IMM - Institut Mutualiste de Montsouris
8 Régulation spatiale des Génomes - Spatial Regulation of Genomes
9 IVI - Interactions Virus-Insectes - Insect-Virus Interactions
10 Virologie Structurale - Structural Virology
11 EMAE - Epidémiologie et modélisation de la résistance aux antimicrobiens - Epidemiology and modelling of bacterial escape to antimicrobials
12 AP-HP - Hôpital Bichat - Claude Bernard [Paris]
13 Department of Internal Medicine, National Referral Center for Rare Systemic Autoimmune Diseases, Assistance Publique Hôpitaux de Paris-Centre (APHP-CUP), Université de Paris, Paris, France
14 PARCC (UMR_S 970/ U970) - Paris-Centre de Recherche Cardiovasculaire
15 Centre d’Investigation Clinique Plurithématique (CIC - P) - CIC Strasbourg
16 CNRS-UMR3569 - Virus et Immunité - Virus and immunity
17 PPR - Plateforme technologique Production et purification de protéines recombinantes – Production and Purification of Recombinant Proteins Technological Platform
18 CRT - Centre de Recherche Translationnelle - Center for Translational Science
19 ICAReB - Investigation Clinique et d’Accès aux Ressources Biologiques (Plate-forme) - Clinical Investigation and Access to BioResources
20 Immunologie Translationnelle - Translational Immunology lab
21 St James's University Hospital
22 Trinity College Dublin
23 Institut Pasteur du Cambodge
24 Epidémiologie des Maladies Emergentes - Emerging Diseases Epidemiology
25 Direction de la recherche médicale de l'Institut Pasteur
26 CNAM - Conservatoire National des Arts et Métiers [CNAM]
27 WEHI - The Walter and Eliza Hall Institute of Medical Research
28 University of Melbourne
29 VRI - Vaccine Research Institute

Background Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) induces a complex antibody response that varies by orders of magnitude between individuals and over time. Methods We developed a multiplex serological test for measuring antibodies to five SARS-CoV-2 antigens and the Spike proteins of seasonal coronaviruses. We measured antibody responses in cohorts of hospitalized patients and healthcare workers followed for up to eleven months after symptoms. A mathematical model of antibody kinetics was used to quantify the duration of antibody responses. Antibody response data were used to train algorithms for estimating time since infection. Results One year after symptoms, we estimate that 36% (95% range: 11%, 94%) of anti-Spike IgG remains, 31% (9%, 89%) anti-RBD IgG remains, and 7% (1%, 31%) anti-Nucleocapsid IgG remains. The multiplex assay classified previous infections into time intervals of 0–3 months, 3–6 months, and 6–12 months. This method was validated using data from a sero-prevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey. Conclusions In addition to diagnosing previous SARS-CoV-2 infection, multiplex serological assays can estimate the time since infection which can be used to reconstruct past epidemics.

Keywords: SARS-SoV-2; antibody kinetics; sero-prevalence; surveillance; time since infection

Domains: Immunology

Stéphane Pelleau, Tom Woudenberg, Jason Rosado, Françoise Donnadieu, Laura Garcia, et al.. Kinetics of the Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Response and Serological Estimation of Time Since Infection. Journal of Infectious Diseases, 2021, 224 (9), pp.1489-1499. ⟨10.1093/infdis/jiab375⟩. ⟨pasteur-03319587v2⟩