Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/45775
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dc.contributor.authorANGELI, Leonardo-
dc.contributor.authorCaetano, Constantino Pereira-
dc.contributor.authorFRANCO, Nicolas-
dc.contributor.authorCOLETTI, Pietro-
dc.contributor.authorFAES, Christel-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorBeutels, Philippe-
dc.contributor.authorABRAMS, Steven-
dc.contributor.authorWILLEM, Lander-
dc.contributor.authorHENS, Niel-
dc.date.accessioned2025-04-01T07:48:22Z-
dc.date.available2025-04-01T07:48:22Z-
dc.date.issued2025-
dc.date.submitted2025-03-26T11:22:15Z-
dc.identifier.citationNature communications, 16 (1) (Art N° 2230)-
dc.identifier.urihttp://hdl.handle.net/1942/45775-
dc.description.abstractUnderstanding 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.-
dc.description.sponsorshipL.A., P.B., and N.H. acknowledge funding from the European Union’s Horizon 2020 research and innovation programme – project EpiPose (Grant agreement number 101003688) and the ESCAPE project (101095619), both funded by the European Union. N.H. further acknowledges support from the VERDI project (101045989), also funded by the European Union. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible. L.A. and N.H. acknowledge funding from the Special Research Fund through the Methusalem project BOF08M01 - phase III. C.P.C. acknowledges the funding by Fundação para a Ciência e a Tecnologia (FCT.BD). L.W. and S.A. acknowledge support from the Research Foundation Flanders (FWO) (ACCELERATE project G059423N). CoMix data collection in Belgium was made possible through funding from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (Grant agreement number 101003688), and with financial support from the National Public Health Institute of Belgium, Sciensano and Janssen Pharmaceuticals. This work reflects only the authors’ view. We extend our gratitude to the research teams at the University of Antwerp, Hasselt University, and the London School of Hygiene and Tropical Medicine, involved in the CoMix study within the EpiPose project, for their invaluable contribution in designing the survey and processing, curating, and collecting the social contact data utilised in our study.-
dc.language.isoen-
dc.publisherNATURE PORTFOLIO-
dc.rightsThe Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or otherthird party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.-
dc.subject.otherHumans-
dc.subject.otherBelgium-
dc.subject.otherChild-
dc.subject.otherAdult-
dc.subject.otherChild, Preschool-
dc.subject.otherAdolescent-
dc.subject.otherYoung Adult-
dc.subject.otherMiddle Aged-
dc.subject.otherAge Factors-
dc.subject.otherPandemics-
dc.subject.otherInfant-
dc.subject.otherMale-
dc.subject.otherFemale-
dc.subject.otherBasic Reproduction Number-
dc.subject.otherCOVID-19-
dc.subject.otherSARS-CoV-2-
dc.titleAssessing the role of children in the COVID-19 pandemic in Belgium using perturbation analysis-
dc.typeJournal Contribution-
dc.identifier.issue1-
dc.identifier.volume16-
local.format.pages14-
local.bibliographicCitation.jcatA1-
dc.description.notesAngeli, L (corresponding author), Hasselt Univ, Data Sci Inst, I Biostat, Hasselt, Belgium.-
dc.description.notesleonardo.angeli@uhasselt.be-
local.publisher.placeHEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.artnr2230-
local.type.programmeH2020-
local.relation.h2020101003688/ 101095619-
dc.identifier.doi10.1038/s41467-025-57087-z-
dc.identifier.pmid40044649-
dc.identifier.isi001439689900023-
dc.contributor.orcidFranco, Nicolas/0000-0003-1688-8342; ANGELI,-
dc.contributor.orcidLeonardo/0000-0002-0555-1587-
local.provider.typewosris-
local.description.affiliation[Angeli, Leonardo; Franco, Nicolas; Coletti, Pietro; Faes, Christel; Molenberghs, Geert; Abrams, Steven; Hens, Niel] Hasselt Univ, Data Sci Inst, I Biostat, Hasselt, Belgium.-
local.description.affiliation[Caetano, Constantino Pereira] Univ Lisbon, Ctr Computat & Stochast Math, Inst Super Tecn, Lisbon, Portugal.-
local.description.affiliation[Franco, Nicolas] Univ Namur, Namur Inst Complex Syst NaXys, Namur, Belgium.-
local.description.affiliation[Franco, Nicolas] Univ Namur, Dept Math, Namur, Belgium.-
local.description.affiliation[Coletti, Pietro] UCLouvain Univ Catholique Louvain, Inst Hlth & Soc IRSS, Brussels, Belgium.-
local.description.affiliation[Molenberghs, Geert] Katholieke Univ Leuven, L BioStat, Leuven, Belgium.-
local.description.affiliation[Beutels, Philippe; Willem, Lander; Hens, Niel] Univ Antwerp, Vaccine & Infect Dis Inst, Ctr Hlth Econ Res & Modelling Infect Dis, Antwerp, Belgium.-
local.description.affiliation[Abrams, Steven; Willem, Lander] Univ Antwerp, Dept Family Med & Populat Hlth FAMPOP, Antwerp, Belgium.-
local.uhasselt.internationalyes-
item.contributorANGELI, Leonardo-
item.contributorCaetano, Constantino Pereira-
item.contributorFRANCO, Nicolas-
item.contributorCOLETTI, Pietro-
item.contributorFAES, Christel-
item.contributorMOLENBERGHS, Geert-
item.contributorBeutels, Philippe-
item.contributorABRAMS, Steven-
item.contributorWILLEM, Lander-
item.contributorHENS, Niel-
item.fullcitationANGELI, Leonardo; Caetano, Constantino Pereira; FRANCO, Nicolas; COLETTI, Pietro; FAES, Christel; MOLENBERGHS, Geert; Beutels, Philippe; ABRAMS, Steven; WILLEM, Lander & HENS, Niel (2025) Assessing the role of children in the COVID-19 pandemic in Belgium using perturbation analysis. In: Nature communications, 16 (1) (Art N° 2230).-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
crisitem.journal.eissn2041-1723-
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