Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset

Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analys...

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Main Authors: Benny Borremans, Amandine Gamble, KC Prager, Sarah K Helman, Abby M McClain, Caitlin Cox, Van Savage, James O Lloyd-Smith
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2020-09-01
Series:eLife
Subjects:
RNA
Online Access:https://elifesciences.org/articles/60122
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spelling doaj-a6657acf4ab24508ad0aaa60188866a92021-05-05T21:29:02ZengeLife Sciences Publications LtdeLife2050-084X2020-09-01910.7554/eLife.60122Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onsetBenny Borremans0https://orcid.org/0000-0002-7779-4107Amandine Gamble1KC Prager2https://orcid.org/0000-0003-0669-0754Sarah K Helman3Abby M McClain4https://orcid.org/0000-0001-5000-4198Caitlin Cox5Van Savage6James O Lloyd-Smith7https://orcid.org/0000-0001-7941-502XEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United States; I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium; Evolutionary Ecology Group, University of Antwerp, Antwerp, BelgiumEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United StatesEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United StatesEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United StatesNational Marine Mammal Foundation, San Diego, United StatesEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United StatesEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United States; Biomathematics Department, University of California, Los Angeles, Los Angeles, United StatesEcology and Evolutionary Biology Department, University of California, Los Angeles, Los Angeles, United StatesUnderstanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post-symptom onset (range 1–40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98–100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in feces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.https://elifesciences.org/articles/60122SARS-CoV-2COVID-19antibody kineticsRNAmeta-analysisdetection probability
collection DOAJ
language English
format Article
sources DOAJ
author Benny Borremans
Amandine Gamble
KC Prager
Sarah K Helman
Abby M McClain
Caitlin Cox
Van Savage
James O Lloyd-Smith
spellingShingle Benny Borremans
Amandine Gamble
KC Prager
Sarah K Helman
Abby M McClain
Caitlin Cox
Van Savage
James O Lloyd-Smith
Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
eLife
SARS-CoV-2
COVID-19
antibody kinetics
RNA
meta-analysis
detection probability
author_facet Benny Borremans
Amandine Gamble
KC Prager
Sarah K Helman
Abby M McClain
Caitlin Cox
Van Savage
James O Lloyd-Smith
author_sort Benny Borremans
title Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
title_short Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
title_full Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
title_fullStr Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
title_full_unstemmed Quantifying antibody kinetics and RNA detection during early-phase SARS-CoV-2 infection by time since symptom onset
title_sort quantifying antibody kinetics and rna detection during early-phase sars-cov-2 infection by time since symptom onset
publisher eLife Sciences Publications Ltd
series eLife
issn 2050-084X
publishDate 2020-09-01
description Understanding and mitigating SARS-CoV-2 transmission hinges on antibody and viral RNA data that inform exposure and shedding, but extensive variation in assays, study group demographics and laboratory protocols across published studies confounds inference of true biological patterns. Our meta-analysis leverages 3214 datapoints from 516 individuals in 21 studies to reveal that seroconversion of both IgG and IgM occurs around 12 days post-symptom onset (range 1–40), with extensive individual variation that is not significantly associated with disease severity. IgG and IgM detection probabilities increase from roughly 10% at symptom onset to 98–100% by day 22, after which IgM wanes while IgG remains reliably detectable. RNA detection probability decreases from roughly 90% to zero by day 30, and is highest in feces and lower respiratory tract samples. Our findings provide a coherent evidence base for interpreting clinical diagnostics, and for the mathematical models and serological surveys that underpin public health policies.
topic SARS-CoV-2
COVID-19
antibody kinetics
RNA
meta-analysis
detection probability
url https://elifesciences.org/articles/60122
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