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在异质网络上对传染病动力学进行建模。

Modeling epidemics dynamics on heterogenous networks.

机构信息

Department of Physics, Bar Ilan University, Ramat Gan 52900, Israel.

出版信息

J Theor Biol. 2010 May 21;264(2):197-204. doi: 10.1016/j.jtbi.2010.01.029. Epub 2010 Feb 1.

Abstract

The dynamics of the SIS process on heterogenous networks, where different local communities are connected by airlines, is studied. We suggest a new modeling technique for travelers movement, in which the movement does not affect the demographic parameters characterizing the metapopulation. A solution to the deterministic reaction-diffusion equations that emerges from this model on a general network is presented. A typical example of a heterogenous network, the star structure, is studied in detail both analytically and using agent-based simulations. The interplay between demographic stochasticity, spatial heterogeneity and the infection dynamics is shown to produce some counterintuitive effects. In particular it was found that, while movement always increases the chance of an outbreak, it may decrease the steady-state fraction of sick individuals. The importance of the modeling technique in estimating the outcomes of a vaccination campaign is demonstrated.

摘要

研究了不同局部社区通过航空网络连接的异质网络上 SIS 过程的动力学。我们提出了一种新的旅行者移动建模技术,其中移动不会影响描述人口统计学的参数。从该模型在一般网络上出现的确定性反应扩散方程的解决方案提出了一种新的旅行者移动建模技术,其中移动不会影响描述人口统计学的参数。从该模型在一般网络上出现的确定性反应扩散方程的解决方案。详细研究了一个异质网络的典型示例,即星形结构,通过基于代理的模拟进行了分析和分析。研究表明,人口统计学随机性、空间异质性和感染动力学之间的相互作用会产生一些违反直觉的效果。特别是,发现尽管移动总是会增加爆发的机会,但它可能会降低稳态患病个体的比例。演示了在估计疫苗接种运动结果时建模技术的重要性。

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