A novel epidemic model coupling the infectious disease with awareness diffusion on multiplex networks

In this paper, we propose a two-layered multiplex network model to characterize the coupling between the infectious disease spreading and disease-related information or awareness diffusion, in which one layer is used to denote the contact network for the disease spreading and the other one represents the propagation of information about the infectious diseases. Meanwhile, the topology between two-layered networks is distinct although each node can appear simultaneously on two networks or the mapping mode between network nodes is one-to-one. Through the microscopic Markov chain approach (MMCA), we build the probability transition tree among 6 possible states and the corresponding dynamical equations. After that, we analytically derive the epidemic threshold by the MMCA method, which has been correlated with the network topology, the information diffusion mechanism and the coupling properties between two kinds of spreading dynamics. Finally, we perform extensive numerical simulations to demonstrate the analytical predictions, and in particular we find that self perception can greatly reduce the disease outbreaks. Current results are helpful to deeply understand the spreading behaviors among the real-world population.