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dc.contributor.authorKayano, Taishien
dc.contributor.authorLee, Hyojungen
dc.contributor.authorKinoshita, Ryoen
dc.contributor.authorNishiura, Hiroshien
dc.contributor.alternative茅野, 大志ja
dc.contributor.alternative木下, 諒ja
dc.contributor.alternative西浦, 博ja
dc.date.accessioned2023-02-16T02:19:45Z-
dc.date.available2023-02-16T02:19:45Z-
dc.date.issued2021-01-
dc.identifier.urihttp://hdl.handle.net/2433/279284-
dc.description.abstractObjective Even with relatively high vaccination coverage, Japan experienced rubella epidemics in 2012-2014 and 2018-2019, which were fueled by untraced imported cases. We aimed to develop a risk map for rubella epidemics in Japan by geographic location via analysis of seroepidemiological data and accounting for the abundance of foreign visitors. Methods Geographic age distribution and seroprevalence were used to compute the age- and sex-dependent next-generation matrix in each region. We computed the probability of a major epidemic using the assumed number of untraced imported rubella cases proportionally modeled to the number of foreign travelers. Results Risks of a major epidemic were high in areas with capital cities, while areas with a greater fraction of older people yielded smaller effective reproduction numbers, a lower volume of foreign travelers, and thus a lower probability of a major epidemic. The volume of susceptible adult males was larger in urban geographic regions, having a greater number of foreign travelers than remote areas. Conclusions Our findings are consistent with the observation of multiple large clusters of rubella cases in urban areas during 2012-2014 and 2018-2019. Should a future rubella epidemic occur, it will likely be in geographic areas with capital cities.en
dc.language.isoeng-
dc.publisherElsevier BVen
dc.rights© 2020 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.en
dc.rightsThis is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).en
dc.rights.urihttp://creativecommons.org/licenses/by-ncnd/4.0/-
dc.subjectRubella virusen
dc.subjectImportationen
dc.subjectStatistical modelen
dc.subjectTravelen
dc.subjectEpidemiologyen
dc.subjectVaccinationen
dc.titleIdentifying geographic areas at risk of rubella epidemics in Japan using seroepidemiological dataen
dc.typejournal article-
dc.type.niitypeJournal Article-
dc.identifier.jtitleInternational Journal of Infectious Diseasesen
dc.identifier.volume102-
dc.identifier.spage203-
dc.identifier.epage211-
dc.relation.doi10.1016/j.ijid.2020.09.1458-
dc.textversionpublisher-
dc.identifier.pmid33010463-
dcterms.accessRightsopen access-
datacite.awardNumber17H04701-
datacite.awardNumber19K19343-
datacite.awardNumber18J21587-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-17H04701/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-19K19343/-
datacite.awardNumber.urihttps://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-18J21587/-
dc.identifier.pissn1201-9712-
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.funderName日本学術振興会ja
jpcoar.awardTitle感染者隔離効果の推定手法開発と隔離の有効性メカニズムの解明ja
jpcoar.awardTitleModeling the potential impact of vaccination on Ebola virus disease epidemicen
jpcoar.awardTitleワクチン予防可能疾患の集団免疫度に関する評価体系の構築ja
出現コレクション:学術雑誌掲載論文等

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