论文标题
预测网络上流行病的速度
Predicting the speed of epidemics spreading on networks
论文作者
论文摘要
全球运输和通信网络使现在的信息，思想和传染病现在以远远超出历史上的速度。为了有效地监测，设计或干预此类流行病的过程，有必要预测特定网络中特定传染的速度，并区分在爆发期间迟早会感染的节点。在这里，我们使用消息通话方法研究这些数量，以得出简单有效的预测，这些预测对具有良好一致的各种现实世界网络上的流行病模拟进行了验证。除了对不同节点的个性化预测外，随着触及次数的发展，我们发现从低密度到几乎完全网络饱和的总体突然过渡。我们的理论是在类似树状网络的简单传播的设置中开发和解释的，但是我们还能够展示该方法如何非常适合复杂的传播和高度聚集的网络。
Global transport and communication networks enable information, ideas and infectious diseases now to spread at speeds far beyond what has historically been possible. To effectively monitor, design, or intervene in such epidemic-like processes, there is a need to predict the speed of a particular contagion in a particular network, and to distinguish between nodes that are more likely to become infected sooner or later during an outbreak. Here, we study these quantities using a message-passing approach to derive simple and effective predictions which are validated against epidemic simulations on a variety of real-world networks with good agreement. In addition to individualized predictions for different nodes, we find an overall sudden transition from low density to almost full network saturation as the contagion develops in time. Our theory is developed and explained in the setting of simple contagions on tree-like networks, but we are also able to show how the method extends remarkably well to complex contagions and highly clustered networks.
