Epidemic spreading in multiplex networks with heterogeneous infection rate

Abstract

The awareness behaviour prevents infection, and the epidemic spreading affects awareness spreading. The interactions between human awareness and epidemic spreading are often described in terms of multiplex networks. Many studies have revealed the heterogeneity of infection rates due to different health habits, social conditions, physical strength, and contact frequency between individuals. In this paper, we consider the epidemic spreading process in multiplex networks with heterogeneous infection rate. We construct a heterogeneous infection rate function whose tunable power exponent is related to the degree of the node. The epidemic threshold is obtained by the Markov chain and mean-field approach. Numerical simulations of scale-free, small-world and random networks show that the fraction of infected individuals and epidemic threshold are affected by the power exponent, and the negative heterogeneous infection rate is more conducive to preventing epidemic. Immunization of hub nodes is a good method to mitigate an epidemic.