Virus and information spreading dynamics widely exist in complex systems. However, systematic study still lacks for the interacting spreading dynamics between the two types of dynamics. This paper proposes a mathematical model on multiplex networks, which considers the heterogeneous susceptibility and infectivity in two subnetworks. By using a heterogeneous mean-field theory, we studied the dynamic process and outbreak threshold of the system. Through extensive numerical simulations on artificial networks, we find that the virus’s spreading dynamics can be suppressed by increasing the information spreading probability, decreasing the protection power, or decreasing the susceptibility and infectivity.

中文翻译：

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多重网络上的病毒信息协同进化传播动力学

病毒和信息传播动力学广泛存在于复杂的系统中。但是，对于两种类型的动力学之间相互作用的传播动力学仍然缺乏系统的研究。本文提出了一种基于多重网络的数学模型，该模型考虑了两个子网中的异构易感性和传染性。通过使用异构均值场理论，我们研究了系统的动态过程和爆发阈值。通过在人工网络上进行的大量数值模拟，我们发现可以通过增加信息的传播概率，降低保护能力或降低敏感性和传染性来抑制病毒的传播动力学。