Evidence map›Paper›PMID 40044649›Full record

ArticleNature communications2025

Assessing the role of children in the COVID-19 pandemic in Belgium using perturbation analysis.

Leonardo Angeli, Constantino Pereira Caetano, Nicolas Franco, Pietro Coletti, Christel Faes, Geert Molenberghs, Philippe Beutels, Steven Abrams, Lander Willem, Niel Hens

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

10 authors.

Leonardo AngeliData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium. leonardo.angeli@uhasselt.be.ORCID http://orcid.org/0000-0002-0555-1587
Constantino Pereira CaetanoCenter for Computational and Stochastic Mathematics, Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal.
Nicolas FrancoData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
Pietro ColettiData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.ORCID http://orcid.org/0000-0001-9935-1692
Christel FaesData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
Geert MolenberghsData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.
Philippe BeutelsCentre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.ORCID http://orcid.org/0000-0001-5034-3595
Steven AbramsData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.ORCID http://orcid.org/0000-0001-7353-9304
Lander WillemCentre for Health Economics Research and Modelling Infectious Diseases, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.ORCID http://orcid.org/0000-0002-9210-1196
Niel HensData Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium.ORCID http://orcid.org/0000-0003-1881-0637

Funding

Bijzonder Onderzoeksfonds (Special Research Fund) BOF08M01EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 101003688Fonds Wetenschappelijk Onderzoek (Research Foundation Flanders) G059423N
6 · The paper itself

Abstract

Understanding the evolving role of different age groups in virus transmission is essential for effective pandemic management. We investigated SARS-CoV-2 transmission in Belgium from November 2020 to February 2022, focusing on age-specific patterns. Using a next generation matrix approach integrating social contact data and simulating population susceptibility evolution, we performed a longitudinal perturbation analysis of the effective reproduction number to unravel age-specific transmission dynamics. From November to December 2020, adults in the [18, 60) age group were the main transmission drivers, while children contributed marginally. This pattern shifted between January and March 2021, when in-person education resumed, and the Alpha variant emerged: children aged under 12 years old were crucial in transmission. Stringent social distancing measures in March 2021 helped diminish the noticeable contribution of the [18, 30) age group. By June 2021, as the Delta variant became the predominant strain, adults aged [18, 40) years emerged as main contributors to transmission, with a resurgence in children's contribution during September-October 2021. This study highlights the effectiveness of our methodology in identifying age-specific transmission patterns.

Indexed as

COVID-19SARS-CoV-2AdolescentAdultAge FactorsBasic Reproduction NumberBelgiumChildChild, PreschoolFemaleHumansInfantMaleMiddle AgedPandemicsPhysical Distancing

Identifiers

PMID40044649
PMCPMC11882900

What OpenQuestion holds

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LicenceCC BY
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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.