Robust oscillations in SIS epidemics on adaptive networks: Coarse graining by automated moment closure
Robust oscillations in SIS epidemics on adaptive networks: Coarse graining by automated moment closure
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DOI：
10.1209/0295-5075/82/38004
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发表时间：
2008-05-01
期刊：
影响因子：
1.8
通讯作者：
Kevrekidis, I. G.
中科院分区：
文献类型：
--
作者：
Gross, T.;Kevrekidis, I. G.
我们在一个自适应网络上研究了流行病易感感染易感(SIS)模型的动力学。该模型将流行病传播(网络上的动力学)与网络连接的重新布线(网络的拓扑演变)结合在一起。我们提出并实现了一种计算方法，使我们能够在紧急的、粗粒度的水平上直接研究网络的动力学。该方法避开了闭合低维近似的推导。我们的研究表明，通过人群对疾病的感知进入的全局耦合可以导致网络状态和拓扑的强健大幅度振荡。版权所有(C)Epla，2008。
We investigate the dynamics of an epidemiological susceptible-infected-susceptible (SIS) model on an adaptive network. This model combines epidemic spreading (dynamics on the network) with rewiring of network connections (topological evolution of the network). We propose and implement a computational approach that enables us to study the dynamics of the network directly on an emergent, coarse-grained level. The approach sidesteps the derivation of closed low-dimensional approximations. Our investigations reveal that global coupling, which enters through the awareness of the population to the disease, can result in robust large-amplitude oscillations of the state and topology of the network. Copyright (C) EPLA, 2008.