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タイトル: Identifying geographic areas at risk of rubella epidemics in Japan using seroepidemiological data
著者: Kayano, Taishi
Lee, Hyojung
Kinoshita, Ryo
Nishiura, Hiroshi  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-0941-8537 (unconfirmed)
著者名の別形: 茅野, 大志
木下, 諒
西浦, 博
キーワード: Rubella virus
Importation
Statistical model
Travel
Epidemiology
Vaccination
発行日: Jan-2021
出版者: Elsevier BV
誌名: International Journal of Infectious Diseases
巻: 102
開始ページ: 203
終了ページ: 211
抄録: Objective 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.
著作権等: © 2020 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-ncnd/4.0/).
URI: http://hdl.handle.net/2433/279284
DOI(出版社版): 10.1016/j.ijid.2020.09.1458
PubMed ID: 33010463
出現コレクション:学術雑誌掲載論文等

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