A practical guide to mathematical methods for estimating infectious disease outbreak risks

被引:12
作者
Southall, E. [1 ,2 ]
Ogi-Gittins, Z. [1 ,2 ]
Kaye, A. R. [1 ,2 ]
Hart, W. S. [3 ]
Lovell-Read, F. A. [3 ]
Thompson, R. N. [1 ,2 ]
机构
[1] Univ Warwick, Math Inst, Coventry, England
[2] Univ Warwick, Zeeman Inst Syst Biol & Infect Dis Epidemiol Res, Coventry, England
[3] Univ Oxford, Math Inst, Oxford, England
基金
英国工程与自然科学研究理事会; 英国生物技术与生命科学研究理事会;
关键词
Mathematical modelling; Infectious disease epidemiology; Major outbreak; Branching process; REALISTIC DISTRIBUTIONS; NETWORK STRUCTURE; EPIDEMIC MODELS; MAJOR OUTBREAK; TRANSMISSION; EMERGENCE; COVID-19; HETEROGENEITY; PROBABILITY; EVOLUTION;
D O I
10.1016/j.jtbi.2023.111417
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Mathematical models are increasingly used throughout infectious disease outbreaks to guide control measures. In this review article, we focus on the initial stages of an outbreak, when a pathogen has just been observed in a new location (e.g., a town, region or country). We provide a beginner's guide to two methods for estimating the risk that introduced cases lead to sustained local transmission (i.e., the probability of a major outbreak), as opposed to the outbreak fading out with only a small number of cases. We discuss how these simple methods can be extended for epidemiological models with any level of complexity, facilitating their wider use, and describe how estimates of the probability of a major outbreak can be used to guide pathogen surveillance and control strategies. We also give an overview of previous applications of these approaches. This guide is intended to help quantitative researchers develop their own epidemiological models and use them to estimate the risks associated with pathogens arriving in new host populations. The development of these models is crucial for future outbreak preparedness. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".
引用
收藏
页数:12
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