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タイトル: When Do Epidemics End? Scientific Insights from Mathematical Modelling Studies
著者: Linton, Natalie M.
Lovell-Read, Francesca A.
Southall, Emma
Lee, Hyojung
Akhmetzhanov, Andrei R.
Thompson, Robin N.
Nishiura, Hiroshi  KAKEN_id  orcid https://orcid.org/0000-0003-0941-8537 (unconfirmed)
著者名の別形: 西浦, 博
キーワード: epidemics
disease elimination
infectious disease
end-of-outbreak declaration
epidemiological modelling
発行日: Jun-2022
出版者: Brepols Publishers NV
誌名: Centaurus
巻: 64
号: 1
開始ページ: 31
終了ページ: 60
抄録: Quantitative assessments of when infectious disease outbreaks end are crucial, as resources targeted towards outbreak responses typically remain in place until outbreaks are declared over. Recent improvements and innovations in mathematical approaches for determining when outbreaks end provide public health authorities with more confidence when making end-of-outbreak declarations. Although quantitative analyses of outbreaks have a long history, more complex mathematical and statistical methodologies for analysing outbreak data were developed early in the 20th century and continue to be refined. Historically, such methodologies focused primarily on factors affecting the early and middle phases of an outbreak, with less attention given to determining how and when outbreaks end. This review discusses mathematical modelling methods from the last 20 years that have been developed for determining the ends of infectious disease outbreaks, and considers factors that affect the accuracy of such determinations. When disease surveillance systems provide timely and representative data to inform models, the timings of end-of-outbreak declarations can be fine-tuned to allow outbreaks to be declared over quickly and with a low risk of being incorrect. Premature declarations that outbreaks are over can undermine earlier achievements in disease control and may result in a resurgence of cases, but unnecessary delays in declaring outbreaks over can cause significant economic and social harm. Appropriate declarations that balance the benefits of relaxing control measures against the risk of a surge in cases allow public health resources to be conserved (and economic and social pressures to be reduced) while limiting the potential for additional transmission.
著作権等: © 2022, The Author(s). Published by Brepols Publishers
This is an open access article made available under a CC by 4.0 International License.
URI: http://hdl.handle.net/2433/279168
DOI(出版社版): 10.1484/j.cnt.5.130125
出現コレクション:学術雑誌掲載論文等

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