Optimal discrete resource allocation on metapopulation networks for suppressing spatial spread of epidemic

Abstract

Suppressing an epidemic among regions within limited medical resources has attracted widespread attention but remains challenges. Thereby, within a fixed budget, a reasonable strategy for resource deployment inevitably plays a significant role on constraining the epidemic. In this paper, a metapopulation network model is constructed to simulate the spatial evolution of the epidemic coupled with the discrete resource descriptions, which are mapped to the parameters with binary scopes. Besides, to obtain the optimal resource deployment, we adopt the Binary Particle Swarm Optimization (BPSO) algorithm to search the optimal solution. Experimental results show that BPSO can achieve effective discrete resource deployment, and its solution is significantly better than random allocation of resource. When the budget is low, the vaccine resources are allocated preferentially, with few curative resources allocated. With the budget increasing, all the patches are almost filled with the vaccine resources, and the curative resources are gradually allocated. In addition, under limited budget, the resources are allocated into patches by a scattered manner, and the network with intensive community structure or not has few impacts on resource allocation, which further implies that resources cannot be over concentrated in contiguous areas.