A Dynamic Population Model of Strategic Interaction and Migration under Epidemic Risk

TL;DR

This paper models how individuals' strategic interactions and migration decisions influence epidemic spread using a dynamic population game over multiple zones, highlighting the importance of behavior in epidemic control.

Contribution

It introduces a novel dynamic population game framework incorporating strategic migration and interaction decisions in an epidemic context.

Findings

Strategic behavior significantly impacts epidemic progression.

Migration decisions affect the effectiveness of interventions.

Awareness levels influence agents' responses and epidemic outcomes.

Abstract

In this paper, we show how a dynamic population game can model the strategic interaction and migration decisions made by a large population of agents in response to epidemic prevalence. Specifically, we consider a modified susceptible-asymptomatic-infected-recovered (SAIR) epidemic model over multiple zones. Agents choose whether to activate (i.e., interact with others), how many other agents to interact with, and which zone to move to in a time-scale which is comparable with the epidemic evolution. We define and analyze the notion of equilibrium in this game, and investigate the transient behavior of the epidemic spread in a range of numerical case studies, providing insights on the effects of the agents' degree of future awareness, strategic migration decisions, as well as different levels of lockdown and other interventions. One of our key findings is that the strategic behavior of agents plays an important role in the progression of the epidemic and can be exploited in order to design suitable epidemic control measures.