Evidence map›Paper›PMID 41628173›Full record

ArticlePloS one2026

Factors influencing SARS-CoV-2 IgG test sensitivity: A Bayesian analysis of seroconversion and seroreversion by time since infection, test, age and disease severity.

Toon Braeye, Steven Abrams, Niel Hens

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Toon BraeyeDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.ORCID https://orcid.org/0000-0002-5637-4613
Steven AbramsInteruniversity Institute for Biostatistics and statistical Bioinformatics (I-Biostat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium.
Niel HensInteruniversity Institute for Biostatistics and statistical Bioinformatics (I-Biostat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAntibody testing is commonly used to assess past exposure to pathogens, but the interpretation is complex. We quantified test-specific SARS-CoV-2 seroconversion and seroreversion by time since PCR-confirmed infection, age and disease severity.

methodsWe combined Belgian data from laboratory SARS-CoV-2 testing, prescriptions, contact tracing and hospital surveillance collected between March 2020 and June 2021 with data from published longitudinal studies on Wantai and EuroImmun IgG serological tests. We used a hierarchical Bayesian model to estimate time-varying sensitivity of serological tests following PCR-confirmed infection. The model employed a scaled Weibull-bi-exponential distribution. We accounted for disease severity (distinguishing between asymptomatic, symptomatic, and hospitalized cases), age (i.e., age groups 18-49, 50-64, and 65-74 years) and serological test used.

resultsWe included 44,262 serological test results: 10,864 obtained from published studies, 33,398 from Belgian laboratories. Seroconversion occurred during the six weeks following a PCR-confirmed infection. Age, disease severity and the test used strongly influenced seroconversion rates and the rate of the subsequent seroreversion. For the EuroImmun test, 82% (95% Credible Interval (CrI): 80%-84%) of symptomatic individuals in the youngest age group seroconverted, compared to 95% (CrI: 95%-96%) for the Wantai test. Seroconversion was associated with hospitalization, (OR = 8.17 (CrI: 5.56-13.72), compared to asymptomatic infection) and older age (OR = 1.65 (CrI: 1.41-1.97), compared to 18-49 year-olds). Slower seroreversion was associated with older age, hospitalization and the Wantai test. At 50 weeks, seropositivity among symptomatic 18-49 year-olds was 64% (CrI: 58%-70%) for the EuroImmun test and 95% (CrI: 94%-96%) for the Wantai test.

conclusionThese findings highlight the need for test-specific, time-varying sensitivity adjustments in seroprevalence studies. Such adjustments are crucial for translating seroprevalence results to cumulative incidence estimates.

Indexed as

COVID-19COVID-19 Serological TestingImmunoglobulin GSARS-CoV-2SeroconversionAdolescentAdultAgedAge FactorsAntibodies, ViralBayes TheoremBelgiumFemaleHumansMaleMiddle AgedAntibodies, ViralImmunoglobulin G

Identifiers

PMID41628173
PMCPMC12863488

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.