Evidence map›Paper›PMID 35143473›Full record

ArticlePLoS biology2022

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

Emilie Finch, Rachel Lowe, Stephanie Fischinger, Michael de St Aubin, Sameed M Siddiqui, Diana Dayal, Michael A Loesche, Justin Rhee, Samuel Beger, Yiyuan Hu and 9 more

Abstract readMulticenter Study
In one paragraph

Article in PLoS biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
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  8. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Emilie FinchCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0002-8225-7533
Rachel LoweCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0003-3939-7343
Stephanie FischingerRagon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, United States of America.ORCID 0000-0003-2307-3379
Michael de St AubinHarvard Humanitarian Initiative, Cambridge, Massachusetts, United States of America.ORCID 0000-0003-4833-6200
Sameed M SiddiquiComputational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.ORCID 0000-0002-0392-7085
Diana DayalSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Michael A LoescheSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Justin RheeSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Samuel BegerSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Yiyuan HuSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Matthew J GluckSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Benjamin MormannSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Mohammad A HasdiandaBrigham and Women's Hospital, Boston, Massachusetts, United States of America.ORCID 0000-0002-3100-9660
Elon R MuskSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Galit AlterRagon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, United States of America.
Anil S MenonSpace Exploration Technologies Corp, Hawthorne, California, United States of America.
Eric J NillesHarvard Humanitarian Initiative, Cambridge, Massachusetts, United States of America.ORCID 0000-0001-7044-5257
Adam J KucharskiCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.
CMMID COVID-19 working group and the SpaceX COVID-19 Cohort Collaborative

Funding

Technology CoreU19AI135995 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI Laura D. Hughes · 2018 to 2026
$32.0M
Demystifying the antiviral activity of the IgG3+ antibody responseR37AI080289 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI ALTER, GALIT · 2015 to 2022
$5.8M
Immunologic Signatures of SARS-CoV-2 Vaccination and DiseaseU01CA260476 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI BAROUCH, DAN H. · 2020 to 2024
$3.7M
SARS-CoV-2 Variant TestingR01AI146785 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI LINGWOOD, DANIEL · 2020 to 2024
$3.3M
CHLAMYDIA PNEUMONIAE AND MACROPHAGES IN ATHEROSCLEROSISR01AI042790 · NIAID · UNIVERSITY OF WISCONSIN MADISON · PI BYRNE, GERALD IRWIN · 1999 to 2003
$983k
CRCNS: Deep Neural Network Approaches for Closed-Loop Deep Brain StimulationR01NS110424 · NINDS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI RICHARDSON, ROBERT MARK, TURNER, ROBERT STERLING · 2018 to 2020
$673k
CGH CDC HHS U01 GH002238Gates Foundation INV-001754Gates Foundation INV-003174Gates Foundation INV-016832Medical Research Council MC_PC_19065Medical Research Council MR/N013638/1Medical Research Council MR/V027956/1NCI NIH HHS U01 CA260476NIAID NIH HHS R01 AI042790NIAID NIH HHS R01 AI146785NIAID NIH HHS R37 AI080289NIAID NIH HHS U19 AI135995NINDS NIH HHS R01 NS110424Wellcome TrustWellcome Trust 206250/Z/17/Z
6 · The paper itself

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.

Indexed as

AdolescentAdultAgedAntibodies, ViralCOVID-19COVID-19 Nucleic Acid TestingCOVID-19 Serological TestingHumansLogistic ModelsMiddle AgedPolymerase Chain ReactionProspective StudiesReinfectionSARS-CoV-2Seroepidemiologic StudiesTime FactorsAntibodies, Viral

Identifiers

PMID35143473
PMCPMC8865659

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.