Examining the impact of emotion-driven resource allocation on information-behavior-disease coupling dynamics

In public emergency management, both medical and informational resources play crucial roles in shaping disease spreading dynamics. To enrich the literature on resource allocation in the context of disease spread, this paper proposes a mUAU-DKD-rSIS model to investigate how emotion-driven resource allocation influences the coupled evolution of rumor dissemination, panic-buying behavior adoption, and disease spreading in multiplex networks. First, we examine the impact of emotional heterogeneity on resource allocation, hypothesizing that anxious individuals tend to provide more informational resources but fewer medical resources than calm individuals. Second, to capture the functional heterogeneity of resources across different individual states, informational resources are classified into learning and review types, while medical resources are divided into protective and curative categories. Third, the source of resources is extended from the individual level to the group level by incorporating common pool resources. Using the microscopic Markov chain approach (MMCA) and numerical simulations, our analysis shows that rational resource allocation is essential for effective disease control. Notably, learning informational resources give rise to a meta-critical point that modulates the coupling strength in multiplex networks. In contrast, curative medical resources exhibit a second-order phase transition and an optimal utilization rate. These findings provide theoretical insights that may inform resource allocation strategies in public health emergencies.