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适用于孤立人群中流行病的幂律。

Power laws governing epidemics in isolated populations.

作者信息

Rhodes C J, Anderson R M

机构信息

Centre for the Epidemiology of Infectious Disease, Department of Zoology, University of Oxford, UK.

出版信息

Nature. 1996 Jun 13;381(6583):600-2. doi: 10.1038/381600a0.

Abstract

Temporal changes in the incidence of measles virus infection within large urban communities in the developed world have been the focus of much discussion in the context of the identification and analysis of nonlinear and chaotic patterns in biological time series. In contrast, the measles records for small isolated island populations are highly irregular, because of frequent fade-outs of infection, and traditional analysis does not yield useful insight. Here we use measurements of the distribution of epidemic sizes and duration to show that regularities in the dynamics of such systems do become apparent. Specifically, these biological systems are characterized by well-defined power laws in a manner reminiscent of other nonlinear, spatially extended dynamical systems in the physical sciences. We further show that the observed power-law exponents are well described by a simple lattice-based model which reflects the social interaction between individual hosts.

摘要

在发达国家的大型城市社区中,麻疹病毒感染发病率的时间变化一直是关于生物时间序列中非线性和混沌模式的识别与分析讨论的焦点。相比之下,由于感染经常消失,小的孤立岛屿人群的麻疹记录非常不规则,传统分析无法提供有用的见解。在这里,我们通过测量疫情规模和持续时间的分布来表明,这类系统动态中的规律确实变得明显。具体而言,这些生物系统以明确的幂律为特征,这让人联想到物理科学中的其他非线性、空间扩展动力系统。我们进一步表明,一个简单的基于格点的模型能够很好地描述观测到的幂律指数,该模型反映了个体宿主之间的社会互动。

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