Discrete-time Markov chain approach to contact-based disease spreading in complex networks
Discrete-time Markov chain approach to contact-based disease spreading in complex networks
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DOI：
10.1209/0295-5075/89/38009
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发表时间：
2010-02-01
期刊：
影响因子：
1.8
通讯作者：
Moreno, Y.
中科院分区：
文献类型：
--
作者：
Gomez, S.;Arenas, A.;Moreno, Y.
网络中的许多传染过程是通过其相连顶点之间的随机接触传播的。在物理学文献中广泛分析了两种极限情况，即所谓的接触过程（CP），其中传染病以一定的速率从一个受感染的顶点一次传播到一个邻居；以及反应过程（RP），在该过程中，一个受感染的个体有效地与它所有的邻居接触以传播传染病。然而，通过考虑单位时间内一定数量的随机接触，从这两种情况之间的插值可以得到一个更现实的情景。在这里，我们提出了一个基于接触的传染病传播问题的离散时间公式。我们解决了一系列由单位时间内随机接触试验次数参数化的模型，这些模型的范围从CP到RP。与常见的异质平均场方法不同，我们关注单个节点的感染概率。利用这个公式，我们可以构建不同感染模型的整个相图并确定它们的关键特性。版权所有（C）EPLA，2010
Many epidemic processes in networks spread by stochastic contacts among their connected vertices. There are two limiting cases widely analyzed in the physics literature, the so-called contact process (CP) where the contagion is expanded at a certain rate from an infected vertex to one neighbor at a time, and the reactive process (RP) in which an infected individual effectively contacts all its neighbors to expand the epidemics. However, a more realistic scenario is obtained from the interpolation between these two cases, considering a certain number of stochastic contacts per unit time. Here we propose a discrete-time formulation of the problem of contact-based epidemic spreading. We resolve a family of models, parameterized by the number of stochastic contact trials per unit time, that range from the CP to the RP. In contrast to the common heterogeneous mean-field approach, we focus on the probability of infection of individual nodes. Using this formulation, we can construct the whole phase diagram of the different infection models and determine their critical properties. Copyright (C) EPLA, 2010