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SIS和SIR随机流行病模型:一种最大熵方法。

The SIS and SIR stochastic epidemic models: a maximum entropy approach.

作者信息

Artalejo J R, Lopez-Herrero M J

机构信息

Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid, 28040 Madrid, Spain.

出版信息

Theor Popul Biol. 2011 Dec;80(4):256-64. doi: 10.1016/j.tpb.2011.09.005. Epub 2011 Oct 12.

Abstract

We analyze the dynamics of infectious disease spread by formulating the maximum entropy (ME) solutions of the susceptible-infected-susceptible (SIS) and the susceptible-infected-removed (SIR) stochastic models. Several scenarios providing helpful insight into the use of the ME formalism for epidemic modeling are identified. The ME results are illustrated with respect to several descriptors, including the number of recovered individuals and the time to extinction. An application to infectious data from outbreaks of extended spectrum beta lactamase (ESBL) in a hospital is also considered.

摘要

我们通过制定易感-感染-易感(SIS)和易感-感染-清除(SIR)随机模型的最大熵(ME)解来分析传染病传播的动态。确定了几种有助于深入了解将ME形式主义用于流行病建模的情况。针对包括康复个体数量和灭绝时间在内的几个描述符说明了ME结果。还考虑了将其应用于医院中广谱β-内酰胺酶(ESBL)暴发的感染数据。

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