Effects of awareness diffusion and self-initiated awareness behavior on epidemic spreading - An approach based on multiplex networks

• The interplay between the epidemic spreading and the diffusion of awareness is studied in multiplex networks.
• Unaware individuals can be informed by aware neighbors in information network and self-awareness induced by the infected neighbors in contact networks.
• The effects of awareness diffusion and self-initiated awareness on the epidemic threshold and the density of infection are investigated.
• Our findings show that the local or global information based self-awareness can reduce the density of infection but cannot alter the epidemic threshold.

In this paper, we study the interplay between the epidemic spreading and the diffusion of awareness in multiplex networks. In the model, an infectious disease can spread in one network representing the paths of epidemic spreading (contact network), leading to the diffusion of awareness in the other network (information network), and then the diffusion of awareness will cause individuals to take social distances, which in turn affects the epidemic spreading. As for the diffusion of awareness, we assume that, on the one hand, individuals can be informed by other aware neighbors in information network, on the other hand, the susceptible individuals can be self-awareness induced by the infected neighbors in the contact networks (local information) or mass media (global information). Through Markov chain approach and numerical computations, we find that the density of infected individuals and the epidemic threshold can be affected by the structures of the two networks and the effective transmission rate of the awareness. However, we prove that though the introduction of the self-awareness can lower the density of infection, which cannot increase the epidemic threshold no matter of the local information or global information. Our finding is remarkably different to many previous results on single-layer network: local information based behavioral response can alter the epidemic threshold. Furthermore, our results indicate that the nodes with more neighbors (hub nodes) in information networks are easier to be informed, as a result, their risk of infection in contact networks can be effectively reduced.