Coupled Dynamics of Information-Epidemic Spreading with Resource Allocation and Transmission on Multi-Layer Networks

The spread of epidemic-associated panic information through online social platforms, as well as the allocation and utilization of therapeutic defensive resources in reality, directly influences the transmission of infectious diseases. Moreover, how to reasonably allocate resources to effectively suppress epidemic spread remains a problem that requires further investigation. To address this, we construct a coupled three-layer network framework to explore the complex co-evolutionary mechanisms among false panic information, therapeutic defensive resource transmission, and disease propagation. In the model, individuals can obtain therapeutic defensive resources either through centralized distribution by government agencies or through interpersonal assistance, while the presence of false panic information reduces the willingness of neighbors to share resources. Using the microscopic Markov chain approach, we formulate the dynamical equations of the system and analyze the epidemic threshold. Furthermore, systematic simulation analyses are carried out to evaluate how panic information, resource-sharing willingness, centralized distribution strategies, and resource effectiveness affect epidemic prevalence and threshold levels. For example, under a representative parameter setting, the infection prevalence decreases from 0.18 under the random allocation strategy to 0.03 when resources are allocated exclusively to infected individuals. Moreover, increasing the total supply of resources under high treatment efficiency raises the epidemic threshold by approximately 2.5 times, effectively delaying the outbreak. These quantitative results highlight the significant role of allocation strategies, resource supply, and treatment efficiency in suppressing epidemic transmission.