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

Authors :
Pelleau S
Woudenberg T
Rosado J
Donnadieu F
Garcia L
Obadia T
Gardais S
Elgharbawy Y
Velay A
Gonzalez M
Nizou JY
Khelil N
Zannis K
Cockram C
Merkling SH
Meola A
Kerneis S
Terrier B
de Seze J
Planas D
Schwartz O
Dejardin F
Petres S
von Platen C
Pellerin SF
Arowas L
de Facci LP
Duffy D
Cheallaigh CN
Dunne J
Conlon N
Townsend L
Duong V
Auerswald H
Pinaud L
Tondeur L
Backovic M
Hoen B
Fontanet A
Mueller I
Fafi-Kremer S
Bruel T
White M
Source :
The Journal of infectious diseases [J Infect Dis] 2021 Nov 16; Vol. 224 (9), pp. 1489-1499.
Publication Year :
2021

Abstract

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.<br />Methods: We developed a multiplex serological test for measuring antibodies to 5 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 11 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.<br />Results: One year after symptoms, we estimate that 36% (95% range, 11%-94%) of anti-Spike immunoglobulin G (IgG) remains, 31% (95% range, 9%-89%) anti-RBD IgG remains, and 7% (1%-31%) of 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 seroprevalence survey in France, demonstrating that historical SARS-CoV-2 transmission can be reconstructed using samples from a single survey.<br />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.<br /> (© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America.)

Details

Language :
English
ISSN :
1537-6613
Volume :
224
Issue :
9
Database :
MEDLINE
Journal :
The Journal of infectious diseases
Publication Type :
Academic Journal
Accession number :
34282461
Full Text :
https://doi.org/10.1093/infdis/jiab375