Epidemic dynamics on temporal complex networks.

Abstract

A wide range of real-world systems, ranging from physical and biological systems to social systems, can be described as temporal networks, where link temporality has profound effects on many dynamical processes taking place on networks. Here we study the susceptible-infected-susceptible model on temporal complex networks, where edges are randomly activated or terminated at each time step. We analytically obtain the epidemic threshold for temporal complex networks with arbitrary initial degree distributions. The approximate endemic equilibrium prevalence for temporal complex networks with arbitrary initial degree distributions is derived analytically for the system close to the epidemic threshold and far away from it. In addition, we demonstrate that the system undergoes a continuous transition from the disease-free state to the endemic state. Our results pave the way to understand how the degree distributions will affect a wide variety of binary-state dynamics on temporal complex networks.