Litcius/Paper detail

Traffic-driven epidemic spreading in multiplex networks

Jie Chen, Mao-Bin Hu, Ming Li

2020Physical review. E36 citationsDOIOpen Access PDF

Abstract

Recent progress on multiplex networks has provided a powerful way to abstract the diverse interaction of a network system with multiple layers. In this paper, we show that a multiplex structure can greatly affect the spread of an epidemic driven by traffic dynamics. One of the interesting findings is that the multiplex structure could suppress the outbreak of an epidemic, which is different from the typical finding of spread dynamics in multiplex networks. In particular, one layer with dense connections can attract more traffic flow and eventually suppress the epidemic outbreak in other layers. Therefore, the epidemic threshold will be larger than the minimal threshold of the layers. With a mean-field approximation, we provide explicit expressions for the epidemic threshold and for the onset of suppressing epidemic spreading in multiplex networks. We also provide the probability of obtaining a multiplex configuration that suppresses the epidemic spreading when the multiplex is composed of: (i) two Erdős-Rényi layers and (ii) two scale-free layers. Therefore, compared to the situation of an isolated network in which a disease may be able to propagate, a larger epidemic threshold can be found in multiplex structures.

Topics & Concepts

MultiplexOutbreakComputer scienceStatistical physicsBiologyPhysicsVirologyBioinformaticsComplex Network Analysis TechniquesOpinion Dynamics and Social InfluenceOpportunistic and Delay-Tolerant Networks