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.

中文翻译：

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流行病风险下战略互动和迁移的动态人口模型

在本文中，我们展示了动态人口博弈如何模拟大量代理为应对流行病而做出的战略交互和迁移决策。具体来说，我们考虑了一个经过修改的易感-无症状-感染-恢复 (SAIR) 流行模型在多个区域。代理选择是否激活（即与他人交互），与多少其他代理交互，以及在与流行病演变相当的时间尺度内移动到哪个区域。我们定义和分析了这个博弈中的均衡概念，并在一系列数值案例研究中研究了流行病传播的瞬态行为，提供了对代理人未来意识程度、战略迁移决策以及不同级别的封锁和其他干预措施。