Congying Liu, Xiaoqun Wu, Xiaoyang Liu, Su Zhong, Zhu Liu
In the era of Information 2.0, the intricate coupling between information diffusion and human behavioral patterns is reshaping the spatiotemporal dynamics of disease transmission, thereby posing substantial challenges to containing the cross-regional spread of epidemics. To address this issue, we modify the classical movement-interaction-return model by incorporating mobility-based detection and then investigate the effects of heterogeneity in mobility patterns, induced by information diffusion and quarantine strategies, on the dynamic behaviors of epidemic spreading in multiplex metapopulation networks. The derived epidemic threshold indicates that epidemic prevention and control measures become ineffective in the thermodynamic limit. Moreover, we identify a counterintuitive paradox that mobility-based detection strategies in metapopulations have little impact on the final prevalence of epidemics. In addition, we discover that controlling the diffusion process of the disease is more effective than controlling its reaction process. Our framework offers a new perspective on the spatiotemporal transmission of diseases in metapopulation networks, which might assist policymakers in designing more effective public health strategies.