SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort
Name
journal.pbio.3001531.pdf
Description
Published version
Size
965.15 KB
Format
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Checksum (MD5)
5761987c1092cf5f0c8417a9dcfd307a
Author(s)
Finch, Emilie
Lowe, Rachel
Fischinger, Stephanie
de St Aubin, Michael
Siddiqui, Sameed M
Dayal, Diana
Loesche, Michael A
Rhee, Justin
Beger, Samuel
Hu, Yiyuan
Date Issued
February 10, 2022
Journal
PLOS Biology
Publisher
Public Library of Science (PLoS)
Citation
Finch E, Lowe R, Fischinger S, de St Aubin M, Siddiqui SM, et al. (2022) SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort. PLOS Biology 20(2): e3001531.
Version
Final published version
Abstract
Identifying the potential for SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4,411 United States employees in 4 states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an odds ratio for reinfection ranging from 0.14 (95% CI: 0.019 to 0.63) to 0.28 (95% CI: 0.05 to 1.1), implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 72% to 86% reduced odds of a subsequent PCR positive test based on our point estimates. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a 6-month time period. We also highlight 2 major sources of bias and uncertainty to be considered when estimating the relative risk of reinfection, confounders and the choice of baseline time point, and show how to account for both in reinfection analysis.
MIT Department
Ragon Institute of MGH, MIT and Harvard
Massachusetts Institute of Technology. Computational and Systems Biology Program
Broad Institute of MIT and Harvard
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1371/journal.pbio.3001531
