Min Byungjoon, Castellano Claudio
Department of Physics, Chungbuk National University, Cheongju, Chungbuk 28644, Republic of Korea.
Istituto dei Sistemi Complessi (ISC-CNR), Via dei Taurini 19, I-00185 Roma, Italy.
Chaos. 2020 Feb;30(2):023131. doi: 10.1063/1.5140813.
The interaction among spreading processes on a complex network is a nontrivial phenomenon of great importance. It has recently been realized that cooperative effects among infective diseases can give rise to qualitative changes in the phenomenology of epidemic spreading, leading, for instance, to abrupt transitions and hysteresis. Here, we consider a simple model for two interacting pathogens on a network and we study it by using the message-passing approach. In this way, we are able to provide detailed predictions for the behavior of the model in the whole phase-diagram for any given network structure. Numerical simulations on synthetic networks (both homogeneous and heterogeneous) confirm the great accuracy of the theoretical results. We finally consider the issue of identifying the nodes where it is better to seed the infection in order to maximize the probability of observing an extensive outbreak. The message-passing approach provides an accurate solution also for this problem.
复杂网络上传播过程之间的相互作用是一种非常重要的非平凡现象。最近人们认识到，传染病之间的协同效应会导致流行病传播现象学的质的变化，例如导致突然转变和滞后现象。在这里，我们考虑一个网络上两种相互作用病原体的简单模型，并使用消息传递方法对其进行研究。通过这种方式，我们能够针对任何给定网络结构在整个相图中为模型的行为提供详细预测。对合成网络（包括均匀网络和非均匀网络）的数值模拟证实了理论结果的高度准确性。我们最后考虑确定在哪些节点上播种感染以最大化观察到大规模爆发概率的问题。消息传递方法也为这个问题提供了精确的解决方案。
