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随机游走者在完整、循环和星形图的复发性种群模型中的传播。

Epidemics of random walkers in metapopulation model for complete, cycle, and star graphs.

机构信息

Department of Mechanical Engineering, Shizuoka University, Hamamatsu 432-8561, Japan.

Department of Mathematical and Systems Engineering, Shizuoka University, Hamamatsu 432-8561, Japan.

出版信息

J Theor Biol. 2018 Aug 7;450:66-75. doi: 10.1016/j.jtbi.2018.04.029. Epub 2018 Apr 25.

Abstract

We present the metapopulation dynamic model for epidemic spreading of random walkers between subpopulations. A subpopulation is represented by a node on a graph. Each agent or individual is either susceptible (S) or infected (I). All agents move by random walk on the graph; namely, each agent randomly determines the destination of migration. The reaction-diffusion equations are presented as ordinary differential equations, not partial differential equations. To evaluate the risk of each subpopulation (node), we obtain the solutions of reaction-diffusion equations analytically and numerically for small, complete, cycle and star graphs. If a graph is homogeneous, or if every node has the same degree, then the solution never changes for any nodes. However, when a graph is heterogeneous, the infection density in equilibrium differs entirely among nodes. For example, on star graphs, the hub seems to be a supply source of disease because the infection density at the hub is much higher than that at the other nodes. On every graph, the epidemic thresholds are identical for all nodes.

摘要

我们提出了一种元种群动态模型,用于研究在亚种群之间随机行走的传染病传播。亚种群由图上的一个节点表示。每个个体要么是易感者(S),要么是感染者(I)。所有个体都通过在图上的随机游走进行移动;也就是说,每个个体随机确定迁移的目的地。反应扩散方程被表示为常微分方程,而不是偏微分方程。为了评估每个亚种群(节点)的风险,我们通过解析和数值方法获得了反应扩散方程在小、完整、循环和星形图上的解。如果一个图是均匀的,或者每个节点的度数都相同,那么对于任何节点,解都不会改变。然而,当一个图是异质的时,平衡时的感染密度在各个节点之间完全不同。例如,在星形图上,中心节点似乎是疾病的供应源,因为中心节点的感染密度远高于其他节点。在每个图上,所有节点的传染病阈值都是相同的。

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