Effective Degree Theory on Multiplex Networks Based on UAP-SIR Model

Epidemic spreading processes on top of multiplex networks have more dynamical properties than on single layered networks. To describe the intertwined processes on such networks, heterogeneous mean field approach (HMF) have been proposed for the continuous-time processes. However, it has been shown that the time evolution of infected individuals and the final epidemic size obtained from this approach have remarkable discrepancy with those from the Monte Carlo simulations. In this paper, we extend effective degree theory (EDT) for analyzing continuous-time epidemic processes on multiplex networks based on SIR epidemic model. Predictions obtained from the theory are shown to have excellent agreement with Monte Carlo simulations.