The effect of role-based resource allocation on epidemic dynamics

TL;DR

This paper introduces a coupled dynamical model for resource allocation in epidemics, revealing how different allocation strategies impact disease prevalence and system stability, with implications for optimizing epidemic response.

Contribution

It presents a novel hierarchical resource allocation model that captures complex epidemic dynamics and uncovers key trade-offs and bistability phenomena.

Findings

Prevalence shows four distinct response patterns to resource allocation.

Trade-off identified between resource efficiency and infection risk.

Cascade-induced bistability emerges in the coupled system.

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.