Impacts of information propagation on epidemic spread over different migration routes

Abstract

Information propagation driven by the epidemic may cause individuals awareness to change their behavior to prevent themselves from being infected, as we observed in reality that aware individuals often migrate away from infected areas. In this work, we study the coupled interaction of epidemic spreading and information propagation over a two-layer metapopulation network, where aware and unaware individuals separately take different migration routes, and mainly explore how individual migration route affects the epidemic spreading. Combined with the transition probability tree of individual states, we use Markovian chain approach to derive the epidemic threshold for the proposed model. Through numerous Monte Carlo simulations, we verify the accuracy of the Markovian equations for the prediction of epidemic dynamics. The results show that the role of information transmission in suppressing the epidemic is limited. Further increase in the information transmission rate beyond some critical value will no longer affect the epidemic. Detailed analysis of information propagation has to consider the migration route of individuals, especially the aware individuals, and their mobility frequency. In addition, the initial population distribution is also a fundamental factor for the epidemic dynamic. With a heterogeneous population distribution, frequent mobility of individuals would delay the epidemic spread, while with the homogeneous population distribution, it does not. The study of the coupled interaction between epidemic and information over separate migration routes provides helpful guidance for the intervention of epidemic in reality.