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.
翻译:在本文中,我们展示了动态人口游戏如何能模拟大批物剂为应对流行病流行而作出的战略互动和移徙决定。具体地说,我们考虑在多个地区采用经修改的易受感染性感染恢复(SAIR)流行病模式。代理商选择是否激活(即与他人互动),与多少其他物剂互动,以及在与流行病演变相类似的时间范围内向哪个区域移动。我们界定并分析这一游戏的平衡概念,并在一系列数字案例研究中调查该流行病传播的短暂行为,就代理人未来认识程度、战略移徙决定以及不同程度的封锁和其他干预措施的影响提供见解。我们的主要发现之一是,代理人的战略行为在流行病蔓延过程中发挥着重要作用,可以用来设计适当的流行病控制措施。