Epidemic spreading in networked metapopulation coupling with activity-driven information dissemination

Abstract The information dissemination profoundly influences epidemic spreading, yet their interplay in time-varying systems remains underexplored. To tackle this issue, firstly, a multilayer time-varying network is established to model the coupled information-epidemic dynamics, which comprises a physical layer structured as networked metapopulation with community-preference migration for epidemic transmission and a virtual layer with activity-driven interactions, including media, for information diffusion. Then, using the Microscopic Markov Chain Approach, the temporal evolution of the system state is captured and the expression of the epidemic threshold is derived. Finally, extensive experiments are conducted to explore the role of information dissemination and human mobility in epidemic propagation. Our findings reveal that information dissemination elevates the epidemic threshold, reducing disease prevalence, with media credibility proving more effective than media quantity in mitigating outbreaks. Community heterogeneity and asymmetric mobility further amplify epidemic and awareness spread, particularly in densely connected regions. This study provides a robust theoretical framework for understanding the feedback loop between the coupled information-epidemic spreading dynamics, providing actionable insights for designing public health interventions in spatially and socially complex environments.