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Dynamical patterns of epidemic outbreaks in complex heterogeneous networks

机译：复杂异构网络中流行病暴发的动态模式

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摘要

We present a thorough inspection of the dynamical behavior of epidemic phenomena in populations with complex and heterogeneous connectivity patterns. We show that the growth of the epidemic prevalence is virtually instantaneous in all networks characterized by diverging degree fluctuations, independently of the structure of the connectivity correlation functions characterizing the population network. By means of analytical and numerical results, we show that the outbreak time evolution follows a precise hierarchical dynamics. Once reached the most highly connected hubs, the infection pervades the network in a progressive cascade across smaller degree classes. Finally, we show the influence of the initial conditions and the relevance of statistical results in single case studies concerning heterogeneous networks. The emerging theoretical framework appears of general interest in view of the recently observed abundance of natural networks with complex topological features and might provide useful insights for the development of adaptive strategies aimed at epidemic containment. (c) 2005 Elsevier Ltd. All rights reserved.
机译：我们目前对具有复杂和异构连接模式的人群中流行现象的动力学行为进行了全面检查。我们表明，在以差异程度波动为特征的所有网络中，流行率的增长实际上是瞬时的，而与表征人口网络的连通性相关函数的结构无关。通过分析和数值结果，我们表明爆发时间的演变遵循精确的分层动力学。一旦到达连接最紧密的集线器，感染就会在较小级别的等级上逐步扩散到整个网络。最后，我们在涉及异构网络的单个案例研究中显示了初始条件的影响和统计结果的相关性。鉴于最近观察到的具有复杂拓扑特征的自然网络的丰富性，新兴的理论框架似乎引起了人们的普遍兴趣，并且可能为开发针对流行病控制的适应性策略提供有用的见识。 （c）2005 Elsevier Ltd.保留所有权利。

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