The effect of role-based resource allocation on epidemic dynamics

Abstract

We propose a coupled dynamical model of resource allocation and epidemic spread, inspired by the hierarchical structure of real-world therapeutic resource allocation. In this framework, network nodes are assigned distinct roles as either resource allocators or resource recipients. As the average number of links per recipient from allocators increases, the prevalence exhibits one of four distinct response patterns across conditions: monotonically increasing, monotonically decreasing, U-shaped trend, or a sudden decrease with large fluctuations. A mechanistic analysis uncovers three central insights: (i) a trade-off between efficient resource allocation and infection risk faced by allocators, (ii) the critical need to avoid resource redundancy when therapeutic efficiency is high, and (iii) the emergence of cascade-induced bistability in the coupled system.

References in corpus (15)

• Epidemic processes in complex networks
• Dynamical interplay between awareness and epidemic spreading in multiplex networks
• Localization and Spreading of Diseases in Complex Networks
• Epidemic thresholds of the Susceptible-Infected-Susceptible model on networks: A comparison of numerical and theoretical results
• Coevolution spreading in complex networks
• Suppressing epidemic spreading in multiplex networks with social-support
• Effective approach to epidemic containment using link equations in complex networks
• Disease-induced resource constraints can trigger explosive epidemics
• Solving the Dynamic Correlation Problem of the Susceptible-Infected-Susceptible Model on Networks
• Optimal Allocation of Resources for Suppressing Epidemic Spreading on Networks
• An efficient strategy to suppress epidemic explosion in heterogeneous metapopulation networks
• Non-trivial Resource Amount Requirement in the Early Stage for Containing Fatal Diseases
• The nature of epidemic criticality in temporal networks
• Multistage onset of epidemics in heterogeneous networks
• The Co-evolution of Cooperation and Epidemic Spreading