A new three-layer metapopulation networks model coupling online-offline social interactions with epidemic spread

The dissemination of epidemic-related information can effectively enhance public awareness of preventive measures and decrease infection risks. However, information dissemination through multiple channels, including both online and offline sources, and the dynamics of information dissemination across these channels are influenced by individual mobility. To address this gap, this study develops a three-layer metapopulation network coupled model that integrates online information dissemination, epidemic spreading, and offline information dissemination. The proposed model systematically investigates the patterns of information dissemination through both online and offline channels, as well as the epidemic reaction-diffusion process driven by individual migration. Furthermore, the social interactions dynamics of both information channels are influenced by migration, manifested as migrated individuals acquire offline information in destination patches and establish online connections with individuals residing there. Theoretical analysis using the Microscopic Markov Chain Approach (MMCA) derives epidemic thresholds, while Monte Carlo (MC) simulations validate the model and examine factors influencing propagation dynamics. Results indicate that migration enhances individuals' offline information acquisition, and accelerates cross-patch online information dissemination. Both online and offline information interactions exert inhibitory effects on epidemic spread, effectively increasing the infection threshold and reducing the outbreak scale. Furthermore, increasing the connectivity and dissemination rate of online information, particularly the information dissemination via weak relationships between patches, can effectively inhibit epidemic outbreaks. Notably, when the suppression effect of information on the epidemic is weak, population migration facilitates epidemic spread. In contrast, when the suppression effect is strong, migration-driven information dissemination significantly reduces the probability of infection, thereby further suppressing the outbreak.