IV．感染症の数理モデルと対策
新型コロナウイルス感染症（coronavirus disease 2019：COVID-19）のような新興感染症の流行下においては，感染症数理モデルを用いた流行データ分析やシナリオ分析が政策判断の核をなす重要なエビデンスとなる．日本ではこれまで広く取り上げられることが少ない領域であったが，COVID-19の世界的な流行により注目の集まる研究分野である．本稿では，COVID-19の疫学的な知見に加えて，感染症数理モデルの基礎的な考え方について述べる．...
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| Published in | 日本内科学会雑誌 Vol. 109; no. 11; pp. 2276 - 2280 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | Japanese |
| Published |
一般社団法人 日本内科学会
10.11.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0021-5384 1883-2083 |
| DOI | 10.2169/naika.109.2276 |
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| Abstract | 新型コロナウイルス感染症（coronavirus disease 2019：COVID-19）のような新興感染症の流行下においては，感染症数理モデルを用いた流行データ分析やシナリオ分析が政策判断の核をなす重要なエビデンスとなる．日本ではこれまで広く取り上げられることが少ない領域であったが，COVID-19の世界的な流行により注目の集まる研究分野である．本稿では，COVID-19の疫学的な知見に加えて，感染症数理モデルの基礎的な考え方について述べる． |
|---|---|
| AbstractList | 新型コロナウイルス感染症（coronavirus disease 2019：COVID-19）のような新興感染症の流行下においては，感染症数理モデルを用いた流行データ分析やシナリオ分析が政策判断の核をなす重要なエビデンスとなる．日本ではこれまで広く取り上げられることが少ない領域であったが，COVID-19の世界的な流行により注目の集まる研究分野である．本稿では，COVID-19の疫学的な知見に加えて，感染症数理モデルの基礎的な考え方について述べる． |
| Author | 鈴木, 絢子 西浦, 博 |
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| Copyright | 2020 一般社団法人 日本内科学会 |
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| DOI | 10.2169/naika.109.2276 |
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| References | 1) Grassly NC, Fraser C: Mathematical models of infectious disease transmission. Nature Reviews Microbiology 6: 477-487, 2008. 4) Endo A, et al: Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China [version 3; peer review: 2 approved]. Wellcome Open Res 5: 67, 2020. 6) Nishiura H, et al: Closed environments facilitate secondary transmission of coronavirus disease 2019 (COVID-19). 2020. medRxiv, 2020.02.28.20029272. 2) Anderson RM, May RM: Oxford University Press, New York. Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, New York, 1991. 9) Nishiura H, et al: Serial interval of novel coronavirus (COVID-19) infections. Int J Infect Dis 93: 284-286, 2020. 3) Imai N, et al: Report 3: Transmissibility of 2019-nCoV. 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-01-25-COVID19-Report-3.pdf (accessed 2020.7.15 5) Hao X, et al: Reconstruction of the full transmission dynamics of COVID-19 in Wuhan. Nature 584: 420-424, 2020. doi: 10.1038/s41586-020-2554-8. 8) Yan P, Chowell G: Quantitative Methods for Investigating Infectious Disease Outbreaks. Springer, 2019. ISBN 978-3-030-21923-9. 7) Lipsitch M, et al: Transmission dynamics and control of severe acute respiratory syndrome. Science 300: 1966-1970, 2003. 10) Linton NM, et al: Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data. J Clin Med 9: 538, 2020. doi: 10.3390/jcm9020538. |
| References_xml | – reference: 3) Imai N, et al: Report 3: Transmissibility of 2019-nCoV. 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-01-25-COVID19-Report-3.pdf (accessed 2020.7.15) – reference: 4) Endo A, et al: Estimating the overdispersion in COVID-19 transmission using outbreak sizes outside China [version 3; peer review: 2 approved]. Wellcome Open Res 5: 67, 2020. – reference: 10) Linton NM, et al: Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data. J Clin Med 9: 538, 2020. doi: 10.3390/jcm9020538. – reference: 9) Nishiura H, et al: Serial interval of novel coronavirus (COVID-19) infections. Int J Infect Dis 93: 284-286, 2020. – reference: 1) Grassly NC, Fraser C: Mathematical models of infectious disease transmission. Nature Reviews Microbiology 6: 477-487, 2008. – reference: 2) Anderson RM, May RM: Oxford University Press, New York. Infectious Diseases of Humans: Dynamics and Control. Oxford University Press, New York, 1991. – reference: 8) Yan P, Chowell G: Quantitative Methods for Investigating Infectious Disease Outbreaks. Springer, 2019. ISBN 978-3-030-21923-9. – reference: 5) Hao X, et al: Reconstruction of the full transmission dynamics of COVID-19 in Wuhan. Nature 584: 420-424, 2020. doi: 10.1038/s41586-020-2554-8. – reference: 6) Nishiura H, et al: Closed environments facilitate secondary transmission of coronavirus disease 2019 (COVID-19). 2020. medRxiv, 2020.02.28.20029272. – reference: 7) Lipsitch M, et al: Transmission dynamics and control of severe acute respiratory syndrome. Science 300: 1966-1970, 2003. |
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| SubjectTerms | 基本再生産数 感染症数理モデル 新型コロナウイルス感染症（COVID-19） |
| Title | IV．感染症の数理モデルと対策 |
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