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首页> 外文期刊>Journal of Mathematical Biology >Dangerous connections: on binding site models of infectious disease dynamics
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Dangerous connections: on binding site models of infectious disease dynamics

机译:危险联系:关于传染病动力学的结合网站模型

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We formulate models for the spread of infection on networks that are amenable to analysis in the large population limit. We distinguish three different levels: (1) binding sites, (2) individuals, and (3) the population. In the tradition of physiologically structured population models, the formulation starts on the individual level. Influences from the 'outside world' on an individual are captured by environmental variables. These environmental variables are population level quantities. A key characteristic of the network models is that individuals can be decomposed into a number of conditionally independent components: each individual has a fixed number of 'binding sites' for partners. The Markov chain dynamics of binding sites are described by only a few equations. In particular, individual-level probabilities are obtained from binding-site-level probabilities by combinatorics while population-level quantities are obtained by averaging over individuals in the population. Thus we are able to characterize population-level epidemiological quantities, such as , r, the final size, and the endemic equilibrium, in terms of the corresponding variables.
机译:我们为感染在网络上的传播建立了模型,可以在大人口限制下进行分析。我们区分了三种不同的水平:(1)结合位点,(2)个体,(3)群体。在传统的生理结构人口模型中,公式从个体层面开始。“外部世界”对个人的影响由环境变量捕捉。这些环境变量是人口水平的数量。网络模型的一个关键特征是,个体可以分解为若干条件独立的组件:每个个体都有固定数量的伙伴“绑定位点”。结合位点的马尔可夫链动力学仅由几个方程描述。特别是,个体水平的概率是通过组合学从结合位点水平的概率中获得的,而群体水平的数量是通过对群体中的个体进行平均来获得的。因此,我们能够根据相应的变量来描述人口水平的流行病学数量,如r、最终规模和地方病平衡。

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