Multiplex networks have been proposed as an effective abstract of real complex systems, ranging from multi-modal urban transportation systems to communication systems. In this paper, we investigate a traffic-driven epidemic model in multiplex networks, and derive a theoretical approach to accurately predict the epidemic threshold of each layer. Our results show that the multiplex structure can produce different effects on the epidemic threshold of layers. Interestingly, one important finding is that the epidemic can be completely suppressed in a certain layer. This phenomenon occurs only when the connectivity of layers is very different, and the traffic flow is heterogeneously distributed over the layers. Therefore, epidemic spreading becomes quite distinct among the layers with different amounts of traffic flow. By using mean-field analysis, an explicit expression is derived to detect this traffic-induced epidemic suppression phenomenon. The accuracy of theoretical prediction is assessed in Erdős–Rnyi and scale-free multiplex networks.

已经提出多路复用网络作为实际复杂系统的有效摘要，范围从多式联运城市交通系统到通信系统。在本文中，我们研究了多路复用网络中流量驱动的流行模型，并推导了一种理论方法来准确预测每一层的流行阈值。我们的结果表明，多重结构可以对各层的流行阈值产生不同的影响。有趣的是，一个重要发现是，可以在特定层次上完全抑制流行病。仅当层的连通性非常不同并且业务流在层上异构分布时，才会出现此现象。因此，在具有不同业务量的各层之间，流行病的传播变得十分明显。通过使用均值场分析，派生出一个明确的表达式来检测这种交通诱发的流行病抑制现象。在Erdős-Rnyi和无标度多重网络中评估了理论预测的准确性。