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SIR 流行病模型隐式最终规模方程的可解性

Solvability of implicit final size equations for SIR epidemic models.

作者信息

Bidari Subekshya, Chen Xinying, Peters Daniel, Pittman Dylanger, Simon Péter L

机构信息

Budapest Semesters in Mathematics, Budapest, Hungary.

Institute of Mathematics, Eötvös Loránd University Budapest, Hungary; Numerical Analysis and Large Networks Research Group, Hungarian Academy of Sciences, Hungary; Budapest Semesters in Mathematics, Budapest, Hungary.

出版信息

Math Biosci. 2016 Oct 29. doi: 10.1016/j.mbs.2016.10.012.

Abstract

Final epidemic size relations play a central role in mathematical epidemiology. These can be written in the form of an implicit equation which is not analytically solvable in most of the cases. While final size relations were derived for several complex models, including multiple infective stages and models in which the durations of stages are arbitrarily distributed, the solvability of those implicit equations have been less studied. In this paper the SIR homogeneous mean-field and pairwise models and the heterogeneous mean-field model are studied. It is proved that the implicit equation for the final epidemic size has a unique solution, and that through writing the implicit equation as a fixed point equation in a suitable form, the iteration of the fixed point equation converges to the unique solution. The Markovian SIR epidemic model on finite networks is also studied by using the generation-based approach. Explicit analytic formulas are derived for the final size distribution for line and star graphs of arbitrary size. Iterative formulas for the final size distribution enable us to study the accuracy of mean-field approximations for the complete graph.

摘要

最终流行规模关系在数学流行病学中起着核心作用。这些关系可以写成一个隐式方程的形式,在大多数情况下该方程无法通过解析求解。虽然已经为几个复杂模型推导了最终规模关系,包括多个感染阶段以及阶段持续时间任意分布的模型,但这些隐式方程的可解性研究较少。本文研究了SIR均匀平均场模型、成对模型和非均匀平均场模型。证明了最终流行规模的隐式方程有唯一解,并且通过将隐式方程写成适当形式的不动点方程,不动点方程的迭代收敛到唯一解。还使用基于生成的方法研究了有限网络上的马尔可夫SIR流行模型。推导了任意大小的线图和星图的最终规模分布的显式解析公式。最终规模分布的迭代公式使我们能够研究完全图的平均场近似的准确性。

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