Contagion dynamics in time-varying metapopulation networks
Contagion dynamics in time-varying metapopulation networks
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DOI：
10.1103/physreve.87.032805
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发表时间：
2013-03-11
影响因子：
2.4
通讯作者：
Perra, Nicola
中科院分区：
文献类型：
--
作者：
Liu, Su-Yu;Baronchelli, Andrea;Perra, Nicola
集合种群框架被广泛的学科采用，以描述系统的良好分离，但连接的亚群。子组或补丁通常表示为网络中的节点，其链接表示它们之间的迁移路线。到目前为止，这些连接大多被认为是静态的，但通常会随着时间的推移而演变。在这里，我们解决这种情况下，通过调查简单的传染过程随时间变化的集合种群网络。我们专注于SIR过程，并确定分析的流动性阈值的活动驱动的网络模型的框架内的流行病蔓延的开始。我们发现与静态网络的情况有很大的不同。该阈值完全由定义瞬时迁移个体的平均数量的动态参数来描述，并且不依赖于静态网络表示的属性。值得注意的是，扩散和传染过程是缓慢的随时间变化的图形比在其聚集的静态同行，流动性阈值甚至两个数量级更大的第一种情况下。所提出的结果证实了考虑复杂网络的时变性质的重要性。DOI：10.1103/PhysRevE.87.032805
The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups or patches are often represented as nodes in a network whose links represent the migration routes among them. The connections have been so far mostly considered as static, but in general evolve in time. Here we address this case by investigating simple contagion processes on time-varying metapopulation networks. We focus on the SIR process and determine analytically the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. We find profound differences from the case of static networks. The threshold is entirely described by the dynamical parameters defining the average number of instantaneously migrating individuals and does not depend on the properties of the static network representation. Remarkably, the diffusion and contagion processes are slower in time-varying graphs than in their aggregated static counterparts, the mobility threshold being even two orders of magnitude larger in the first case. The presented results confirm the importance of considering the time-varying nature of complex networks. DOI: 10.1103/PhysRevE.87.032805