Coupled Epidemic-Information Propagation With Stranding Mechanism on Multiplex Metapopulation Networks

Abstract

Acknowledging the significance of information propagation and individual adaptive behavior has been regarded as an indispensable prerequisite for a complete understanding of epidemic spreading. Recent studies have widely considered the metapopulation model, where epidemics spread over a single layer of physical networks via individual mobility. However, these advances neglected the interventions of accompanied information and individual behavior response related to epidemics. In this article, we develop a coupled epidemic-information propagation model on multiplex metapopulation networks leveraging the microscopic Markov chain (MMC) approach, aiming to explore the spatiotemporal characteristics of epidemic spreading process. Taking the individual adaptive behavior into account, the stranding mechanism based on infection level and medical resources is introduced to capture the population size dynamics during individual mobility among different patches. Theoretical epidemic threshold is analytically derived under the improved framework. Extensive numerical simulations are performed to validate our theoretical analysis and further examine the impacts of information propagation and spreading parameters on epidemic threshold and steady-state prevalence. Our results indicate that both the scale of information diffusion and the specific configuration of spreading parameters can significantly suppress the epidemic prevalence. These findings shed a novel light on theoretical research and decision-making of coupled epidemic-information process in the spatiotemporal perspective.