Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34340
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dc.contributor.authorWILLEM, Lander-
dc.contributor.authorABRAMS, Steven-
dc.contributor.authorLIBIN, Pieter-
dc.contributor.authorBeutels, Philippe-
dc.contributor.authorCOLETTI, Pietro-
dc.contributor.authorKUYLEN, Elise-
dc.contributor.authorPETROF, Oana-
dc.contributor.authorMOGELMOSE, Signe-
dc.contributor.authorWAMBUA, James-
dc.contributor.authorHERZOG, Sereina-
dc.contributor.authorFAES, Christel-
dc.contributor.authorHENS, Niel-
dc.date.accessioned2021-06-23T13:17:34Z-
dc.date.available2021-06-23T13:17:34Z-
dc.date.issued2021-
dc.date.submitted2021-06-17T14:29:32Z-
dc.identifier.citationNature Communications, 12 (1) (Art N° 1524)-
dc.identifier.urihttp://hdl.handle.net/1942/34340-
dc.description.abstractThe COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., "household bubbles". The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation.-
dc.description.abstractThe COVID-19 pandemic caused many governments to impose policies restricting social interactions. A controlled and persistent release of lockdown measures covers many potential strategies and is subject to extensive scenario analyses. Here, we use an individual-based model (STRIDE) to simulate interactions between 11 million inhabitants of Belgium at different levels including extended household settings, i.e., "household bubbles". The burden of COVID-19 is impacted by both the intensity and frequency of physical contacts, and therefore, household bubbles have the potential to reduce hospital admissions by 90%. In addition, we find that it is crucial to complete contact tracing 4 days after symptom onset. Assumptions on the susceptibility of children affect the impact of school reopening, though we find that business and leisure-related social mixing patterns have more impact on COVID-19 associated disease burden. An optimal deployment of the mitigation policies under study require timely compliance to physical distancing, testing and self-isolation. The COVID-19 pandemic caused many governments to impose policies restricting social interactions. Here, the authors implement an age-specific, individual-based model with data on social contacts for the Belgian population and investigate the effect of non-pharmaceutical interventions.-
dc.description.sponsorshipThe authors are very grateful for access to the data from the Belgian Scientific Institute for Public Health, Sciensano, and from the Vaccine & Infectious Disease Institute (VaxInfectio), University of Antwerp. We thank several researchers from the SIMID COVID-19 consortium from the University of Antwerp and Hasselt University for numerous constructive discussions and meetings. L.W., S.A., P.J.K.L. and N.H. gratefully acknowledge support from the Research Foundation Flanders (FWO) (postdoctoral fellowships 1234620N and 1242021N, and RESTORE project G0G2920N). This work also received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (P.C., S.A.H. and N.H., grant number 682540—TransMID project; C.F., P.B. and N.H. grant number 101003688—EpiPose project). P.B. and N.H. acknowledge funding from the Antwerp Study Centre for Infectious Diseases (ASCID) and the Methusalem-Centre of Excellence consortium VAX-IDEA. We used computational resources and services provided by the Flemish Supercomputer Centre (VSC), funded by the FWO and the Flemish Government, with special thanks to the CalcUA-team (FB and SB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.-
dc.language.isoen-
dc.publisherNATURE RESEARCH-
dc.rightsOpen Access 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/ licenses/by/4.0/.-
dc.subject.otherAdolescent-
dc.subject.otherAdult-
dc.subject.otherAged-
dc.subject.otherAged, 80 and over-
dc.subject.otherBelgium-
dc.subject.otherCOVID-19-
dc.subject.otherChild-
dc.subject.otherChild, Preschool-
dc.subject.otherCommunicable Disease Control-
dc.subject.otherDisease Transmission, Infectious-
dc.subject.otherHealth Policy-
dc.subject.otherHospitalization-
dc.subject.otherHumans-
dc.subject.otherInfant-
dc.subject.otherInfant, Newborn-
dc.subject.otherMiddle Aged-
dc.subject.otherModels, Theoretical-
dc.subject.otherPandemics-
dc.subject.otherSARS-CoV-2-
dc.subject.otherSchools-
dc.subject.otherYoung Adult-
dc.subject.otherContact Tracing-
dc.subject.otherFamily Characteristics-
dc.subject.otherQuarantine-
dc.titleThe impact of contact tracing and household bubbles on deconfinement strategies for COVID-19-
dc.typeJournal Contribution-
dc.identifier.issue1-
dc.identifier.volume12-
local.bibliographicCitation.jcatA1-
local.publisher.placeHEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.artnr1524-
dc.identifier.doi10.1038/s41467-021-21747-7-
dc.identifier.pmid33750778-
dc.identifier.isiWOS:000627829600010-
dc.identifier.eissn2041-1723-
local.provider.typePubMed-
local.uhasselt.internationalyes-
item.contributorWILLEM, Lander-
item.contributorABRAMS, Steven-
item.contributorLIBIN, Pieter-
item.contributorBeutels, Philippe-
item.contributorCOLETTI, Pietro-
item.contributorKUYLEN, Elise-
item.contributorPETROF, Oana-
item.contributorMOGELMOSE, Signe-
item.contributorWAMBUA, James-
item.contributorHERZOG, Sereina-
item.contributorFAES, Christel-
item.contributorHENS, Niel-
item.fullcitationWILLEM, Lander; ABRAMS, Steven; LIBIN, Pieter; Beutels, Philippe; COLETTI, Pietro; KUYLEN, Elise; PETROF, Oana; MOGELMOSE, Signe; WAMBUA, James; HERZOG, Sereina; FAES, Christel & HENS, Niel (2021) The impact of contact tracing and household bubbles on deconfinement strategies for COVID-19. In: Nature Communications, 12 (1) (Art N° 1524).-
item.accessRightsOpen Access-
item.fulltextWith Fulltext-
item.validationecoom 2022-
crisitem.journal.eissn2041-1723-
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