Evidence map›Paper›PMID 41787546›Full record

ArticleArchives of public health = Archives belges de sante publique2026

Estimating the incidence of SARS-CoV-2 infections by jointly modelling seroprevalence, hospitalization and mortality data, February 2020 - January 2021, Belgium.

Toon Braeye, Robby De Pauw, Laurence Geebelen, Steven Abrams, Isabelle Desombere, Niel Hens, Naïma Hammami, Mathieu Roelants, An Muylaert, Sereina A Herzog

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Toon BraeyeDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium. toon.braeye@sciensano.be.ORCID http://orcid.org/0000-0002-5637-4613
Robby De PauwDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Laurence GeebelenDepartment of Epidemiology and Public Health, Sciensano, Brussels, Belgium.
Steven AbramsInteruniversity Institute for Biostatistics and statistical Bioinformatics (I-Biostat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium.
Isabelle DesombereLaboratory of Immune Response, Department of Infectious diseases in humans, Sciensano, Brussels, Belgium.
Niel HensInteruniversity Institute for Biostatistics and statistical Bioinformatics (I-Biostat), Data Science Institute (DSI), UHasselt, Hasselt, Belgium.
Naïma HammamiDepartment of Care, Team Infection Prevention and Vaccination, Flemish Community, Brussels, Belgium.
Mathieu RoelantsDepartment of Care, Team Infection Prevention and Vaccination, Flemish Community, Brussels, Belgium.
An MuylaertLabo Nuytinck, Evergem, Belgium.
Sereina A HerzogInstitute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Graz, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBelgium experienced two SARS-CoV-2 epidemic waves in 2020, in spring and autumn. Due to limited testing capacity, restrictive case definitions, asymptomatic infections, and incomplete testing compliance, case counts represent only a lower bound of SARS-CoV-2 infection incidence. We estimated this incidence from February 2020 to January 2021 by jointly modelling seroprevalence and surveillance data.

methodsWe developed a hierarchical Bayesian model that jointly fits seroprevalence, hospitalization, and mortality data to a shared latent incidence curve, represented by a spline. The model accounts for time-varying serological test sensitivity (reflecting seroconversion and seroreversion) using informative priors, and simultaneously estimates test specificity, infection-to-event distributions, and time-varying infection hospitalization rates (IHR) and infection fatality rates (IFR). Seroprevalence data comprised 37,235 samples from two repeated cross-sectional studies: residual laboratory samples tested with the EuroImmun IgG ELISA and blood donor samples tested with the Wantai Ab ELISA. Hospitalization and mortality counts were obtained from national COVID-19 surveillance.

resultsBy early 2021, an estimated 19.0% (95% Credible Interval (CrI) 17.4-20.7), 13.6% (CrI 11.5-15.8) and 10.8% (CrI 8.7-13.2) of the Belgian 18-49, 50-64 and 65-74 year-olds had been infected with SARS-CoV-2. The first wave mostly affected the younger age group, with a peak weekly incidence of 2.0% (CrI 1.7-2.3) late March 2020. The second wave peaked late October 2020 with weekly incidences of 1.6% (CrI 1.2-2.1) among 65-74 year-olds and 2.8% (CrI 2.4-3.3) among 18-49 year-olds. IHR and IFR were considerably higher in older age groups and declined over time. Among 65-74 year-olds IHR declined from 9.9% (CrI 7.3-14.2) to 5.0% (CrI 3.5-7.1) and IFR from 2.8% (CrI 2.0-4.0) to 1.2% (CrI 0.9-1.7).

conclusionAn estimated 16.3% (CrI 15.1-17.4) of the Belgian adult population had been infected with SARS-CoV-2 by early 2021. Joint modelling of seroprevalence and surveillance data provides a framework for estimating infection burden.

Indexed as

Bayesian hierarchical modelCOVID-19IncidenceSARS-CoV-2SeroconversionSeroprevalenceSeroreversionStatistical modellingSurveillance data

Identifiers

PMID41787546
PMCPMC13077845

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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.