Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/96535
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dc.contributorDepartment of Applied Mathematics-
dc.creatorWen, Cen_US
dc.creatorWei, Jen_US
dc.creatorMa, ZFen_US
dc.creatorHe, Men_US
dc.creatorZhao, Sen_US
dc.creatorJi, Jen_US
dc.creatorHe, Den_US
dc.date.accessioned2022-12-07T02:55:20Z-
dc.date.available2022-12-07T02:55:20Z-
dc.identifier.issn2468-0427en_US
dc.identifier.urihttp://hdl.handle.net/10397/96535-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2022 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).en_US
dc.rightsThe following publication Wen, C., Wei, J., Ma, Z. F., He, M., Zhao, S., Ji, J., & He, D. (2022). Heterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimation. Infectious Disease Modelling, 7(2), 1-24 is available at https://doi.org/10.1016/j.idm.2022.02.001.en_US
dc.subjectCOVID-19en_US
dc.subjectEpidemic modelen_US
dc.subjectIncubation perioden_US
dc.subjectTransmissionen_US
dc.titleHeterogeneous epidemic modelling within an enclosed space and corresponding Bayesian estimationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage24en_US
dc.identifier.volume7en_US
dc.identifier.issue2en_US
dc.identifier.doi10.1016/j.idm.2022.02.001en_US
dcterms.abstractSince March 11th, 2020, COVID-19 has been a global pandemic for more than one years due to a long and infectious incubation period. This paper establishes a heterogeneous epidemic model that divides the incubation period into infectious and non-infectious and employs the Bayesian framework to model the ‘Diamond Princess’ enclosed space incident. The heterogeneity includes two different identities, two transmission methods, two different-size rooms, and six transmission stages. This model is also applicable to similar mixed structures, including closed schools, hospitals, and communities. As the COVID-19 pandemic continues, our mathematical modeling can provide management insights to the governments and policymakers on how the COVID-19 disease has spread and what prevention strategies still need to be taken.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationInfectious disease modelling, June 2022, v. 7, no. 2, p. 1-24en_US
dcterms.isPartOfInfectious disease modellingen_US
dcterms.issued2022-06-
dc.identifier.scopus2-s2.0-85126137005-
dc.description.validate202212 bckw-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.pubStatusPublisheden_US
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