Dynamics of epidemic diseases on a growing adaptive network.
Dynamics of epidemic diseases on a growing adaptive network.
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DOI：
10.1038/srep42352
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发表时间：
2017-02-10
影响因子：
4.6
通讯作者：
Gross T
中科院分区：
文献类型：
--
作者：
Demirel G;Barter E;Gross T
静态网络上的流行病研究揭示了网络拓扑特征对疾病流行的重要影响，如度分布的方差，即节点邻居数的分布，以及最大度。在这里，我们分析了一个自适应网络，其中度分布不是独立于流行病，而是通过疾病引起的动态和死亡率在复杂的相互作用中形成的。我们研究了一个网络的动力学，该网络根据优先连接规则增长，而节点同时从网络中删除，由于疾病引起的死亡率。我们使用基于个人的模拟和异构节点近似调查疾病的患病率。我们的研究结果表明，在这个系统中的热力学极限不存在流行病的阈值，而网络的增长和流行病的传播之间的相互作用导致指数网络的任何有限的传染率时，疾病持续存在。
The study of epidemics on static networks has revealed important effects on disease prevalence of network topological features such as the variance of the degree distribution, i.e. the distribution of the number of neighbors of nodes, and the maximum degree. Here, we analyze an adaptive network where the degree distribution is not independent of epidemics but is shaped through disease-induced dynamics and mortality in a complex interplay. We study the dynamics of a network that grows according to a preferential attachment rule, while nodes are simultaneously removed from the network due to disease-induced mortality. We investigate the prevalence of the disease using individual-based simulations and a heterogeneous node approximation. Our results suggest that in this system in the thermodynamic limit no epidemic thresholds exist, while the interplay between network growth and epidemic spreading leads to exponential networks for any finite rate of infectiousness when the disease persists.