Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/111715
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dc.contributorDepartment of Applied Mathematics-
dc.creatorDeng, Yen_US
dc.creatorLin, Hen_US
dc.creatorHe, Den_US
dc.creatorZhao, Yen_US
dc.date.accessioned2025-03-13T02:24:54Z-
dc.date.available2025-03-13T02:24:54Z-
dc.identifier.urihttp://hdl.handle.net/10397/111715-
dc.language.isoenen_US
dc.publisherSpringerOpenen_US
dc.rights© The Author(s) 2024. Open 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 licence, and indicate if changes were made. The images or other third 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/.en_US
dc.rightsThe following publication Deng, Y., Lin, H., He, D. et al. Trending on the use of Google mobility data in COVID-19 mathematical models. Adv Cont Discr Mod 2024, 21 (2024) is available at https://doi.org/10.1186/s13662-024-03816-5.en_US
dc.subjectContact matrixen_US
dc.subjectCOVID-19en_US
dc.subjectGoogle mobility dataen_US
dc.subjectMathematical modelsen_US
dc.subjectThe basic reproduction numberen_US
dc.subjectTransmission rateen_US
dc.titleTrending on the use of google mobility data in COVID-19 mathematical modelsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume2024en_US
dc.identifier.doi10.1186/s13662-024-03816-5en_US
dcterms.abstractGoogle mobility data has been widely used in COVID-19 mathematical modeling to understand disease transmission dynamics. This review examines the extensive literature on the use of Google mobility data in COVID-19 mathematical modeling. We mainly focus on over a dozen influential studies using Google mobility data in COVID-19 mathematical modeling, including compartmental and metapopulation models. Google mobility data provides valuable insights into mobility changes and interventions. However, challenges persist in fully elucidating transmission dynamics over time, modeling longer time series and accounting for individual-level correlations in mobility patterns, urging the incorporation of diverse datasets for modeling in the post-COVID-19 landscape.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvances in continuous and discrete models, 2024, v. 2024, 21en_US
dcterms.isPartOfAdvances in continuous and discrete modelsen_US
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85197532848-
dc.identifier.eissn2731-4235en_US
dc.identifier.artn21en_US
dc.description.validate202502 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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