Percolation and epidemics in random clustered networks
Percolation and epidemics in random clustered networks
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DOI：
10.1103/physreve.80.020901
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发表时间：
2009-08-01
影响因子：
2.4
通讯作者：
Miller, Joel C.
中科院分区：
文献类型：
--
作者：
Miller, Joel C.
传染病传播的社会网络通常是聚集的。由于渗透与流行病传播之间的密切关系，这种网络中的渗透行为可以深入了解传染病动力学。许多作者研究了聚集网络中的渗透或流行病，但网络通常在高节点上包含优先接触。我们引入了一类具有相同优先混合的随机聚类网络和一类随机非聚类网络。与非聚类网络相比，聚类网络中的渗透减少了组件大小并增加了流行阈值。
The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease dynamics. A number of authors have studied percolation or epidemics in clustered networks, but the networks often contain preferential contacts in high degree nodes. We introduce a class of random clustered networks and a class of random unclustered networks with the same preferential mixing. Percolation in the clustered networks reduces the component sizes and increases the epidemic threshold compared to the unclustered networks.