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具有无症状传播的传染病模型的最终规模。

Final Size for Epidemic Models with Asymptomatic Transmission.

机构信息

Departament de Matemàtiques, Universitat Autònoma de Barcelona, Edifici C, Cerdanyola del Vallès, 08193, Barcelona, Spain.

Sorbonne Université, Inria, CNRS, Laboratoire Jacques-Louis Lions UMR7598, Equipe MAMBA, Université de Paris, 75005, Paris, France.

出版信息

Bull Math Biol. 2023 May 8;85(6):52. doi: 10.1007/s11538-023-01159-y.

Abstract

The final infection size is defined as the total number of individuals that become infected throughout an epidemic. Despite its importance for predicting the fraction of the population that will end infected, it does not capture which part of the infected population will present symptoms. Knowing this information is relevant because it is related to the severity of the epidemics. The objective of this work is to give a formula for the total number of symptomatic cases throughout an epidemic. Specifically, we focus on different types of structured SIR epidemic models (in which infected individuals can possibly become symptomatic before recovering), and we compute the accumulated number of symptomatic cases when time goes to infinity using a probabilistic approach. The methodology behind the strategy we follow is relatively independent of the details of the model.

摘要

最终感染规模被定义为整个疫情期间感染的个体总数。尽管它对于预测最终感染人群的比例很重要,但它并不能捕捉到感染人群中哪些人会出现症状。了解这些信息很重要,因为它与疫情的严重程度有关。这项工作的目的是给出一个公式,用于计算整个疫情期间出现症状的总病例数。具体来说,我们专注于不同类型的结构化 SIR 传染病模型(其中感染个体在康复之前可能会出现症状),并使用概率方法计算当时间趋于无穷大时出现症状的病例总数。我们所遵循的策略背后的方法学相对独立于模型的细节。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5425/10167127/09d64e289b49/11538_2023_1159_Fig1_HTML.jpg

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