Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/39965
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dc.contributor.authorENSOY-MUSORO, Chellafe-
dc.contributor.authorNGUYEN, Minh Hanh-
dc.contributor.authorHENS, Niel-
dc.contributor.authorMOLENBERGHS, Geert-
dc.contributor.authorFAES, Christel-
dc.date.accessioned2023-04-24T10:11:05Z-
dc.date.available2023-04-24T10:11:05Z-
dc.date.issued2023-
dc.date.submitted2023-04-05T14:44:05Z-
dc.identifier.citationSpatial and spatio-temporal epidemiology (Print), 45 (Art N° 100568)-
dc.identifier.urihttp://hdl.handle.net/1942/39965-
dc.description.abstractThe rapid spread of COVID-19 worldwide led to the implementation of various non-pharmaceutical interven-tions to limit transmission and hence reduce the number of infections. Using telecom-operator-based mobility data and a spatio-temporal dynamic model, the impact of mobility on the evolution of the pandemic at the level of the 581 Belgian municipalities is investigated. By decomposing incidence, particularly into within-and between-municipality components, we noted that the global epidemic component is relatively more important in larger municipalities (e.g., cities), while the local component is more relevant in smaller (rural) municipalities. Investigation of the effect of mobility on the pandemic spread showed that reduction of mobility has a significant impact in reducing the number of new infections.-
dc.description.sponsorshipNH and CF acknowledge support from the European Union’s Horizon 2020 research and innovation programme - project EpiPose (Grant agreement number 101003688).-
dc.language.isoen-
dc.publisherELSEVIER SCI LTD-
dc.rights2023 Elsevier Ltd. All rights reserved.-
dc.subject.otherCOVID-19-
dc.subject.otherMobility-
dc.subject.otherStochastic prediction-
dc.subject.otherSpatio-temporal dynamic model-
dc.titleSpatio-temporal model to investigate COVID-19 spread accounting for the mobility amongst municipalities-
dc.typeJournal Contribution-
dc.identifier.volume45-
local.format.pages8-
local.bibliographicCitation.jcatA1-
dc.description.notesNguyen, MH (corresponding author), Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Data Sci Inst, Hasselt, Belgium.-
dc.description.notesminhhanh.nguyen@uhasselt.be; christel.faes@uhasselt.be-
local.publisher.placeTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND-
local.type.refereedRefereed-
local.type.specifiedArticle-
local.bibliographicCitation.artnr100568-
local.type.programmeH2020-
local.relation.h2020101003688-
dc.identifier.doi10.1016/j.sste.2023.100568-
dc.identifier.isi000947988000001-
local.provider.typewosris-
local.description.affiliation[Ensoy-Musoro, Chellafe; Nguyen, Minh Hanh; Hens, Niel; Molenberghs, Geert; Faes, Christel] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Data Sci Inst, Hasselt, Belgium.-
local.description.affiliation[Hens, Niel] Univ Antwerp, Vaccine & Infect Dis Inst VAXINFECTIO, Ctr Hlth Econ Res & Modelling Infect Dis CHERMID, Antwerp, Belgium.-
local.description.affiliation[Molenberghs, Geert] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, Leuven, Belgium.-
local.uhasselt.internationalno-
item.accessRightsOpen Access-
item.fullcitationENSOY-MUSORO, Chellafe; NGUYEN, Minh Hanh; HENS, Niel; MOLENBERGHS, Geert & FAES, Christel (2023) Spatio-temporal model to investigate COVID-19 spread accounting for the mobility amongst municipalities. In: Spatial and spatio-temporal epidemiology (Print), 45 (Art N° 100568).-
item.contributorENSOY-MUSORO, Chellafe-
item.contributorNGUYEN, Minh Hanh-
item.contributorHENS, Niel-
item.contributorMOLENBERGHS, Geert-
item.contributorFAES, Christel-
item.fulltextWith Fulltext-
crisitem.journal.issn1877-5845-
crisitem.journal.eissn1877-5853-
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