SARS-CoV-2 antibodies protect against reinfection for at least 6 months in a multicentre seroepidemiological workplace cohort.

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...

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Main Authors: Emilie Finch, Rachel Lowe, Stephanie Fischinger, Michael de St Aubin, Sameed M Siddiqui, Diana Dayal, Michael A Loesche, Justin Rhee, Samuel Beger, Yiyuan Hu, Matthew J Gluck, Benjamin Mormann, Mohammad A Hasdianda, Elon R Musk, Galit Alter, Anil S Menon, Eric J Nilles, Adam J Kucharski, CMMID COVID-19 working group and the SpaceX COVID-19 Cohort Collaborative
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-02-01
Series:PLoS Biology
Online Access:https://journals.plos.org/plosbiology/article/file?id=10.1371/journal.pbio.3001531&type=printable
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Summary: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.
ISSN:1544-9173
1545-7885