Wei Zhiyuan, Zhuang Jun
Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, New York, USA.
Risk Anal. 2023 Nov;43(11):2298-2311. doi: 10.1111/risa.14093. Epub 2023 Jan 12.
The adoption of behavioral nonpharmaceutical interventions (NPIs) among the public is essential for tackling the COVID-19 pandemic, yet presents challenges due to the complexity of human behaviors. A large body of literature has utilized classic game theory to investigate the population's decisions regarding the adoption of interventions, where the static solution concept such as the Nash equilibrium is studied. However, individual adoption behavior is not static, instead it is a dynamic process that involves the strategic interactions with other counterparts over time. The study of quantitatively analyzing the dynamics on precautionary behavior during an outbreak is rather scarce. This article fills the research gap by developing an evolutionary game-theoretic framework to model the dynamics of population behavior on the adoption of NPI. We construct the two-group asymmetric game, where behavioral change for each group is characterized by replicator equations. Sensitivity analyses are performed to examine the long-term stability of equilibrium points with respect to perturbation of model parameters. We found that the limiting behavior of intervention adoption in the population consists of only pure strategies in a game setting, indicating that the evolutionary outcome is that everyone either takes up the preventive measure or not. We also applied the framework to examine the mask-wearing behavior, and validated with actual data. Overall, this article provides insights into population dynamics on the adoption of intervention strategy during the outbreak, which can be beneficial for policy makers to better understand the evolutionary trajectory of population behavior.
在公众中采用行为性非药物干预措施(NPIs)对于应对新冠疫情至关重要,但由于人类行为的复杂性,这也带来了挑战。大量文献利用经典博弈论来研究民众关于采用干预措施的决策,其中研究了诸如纳什均衡等静态解概念。然而,个体的采用行为并非静态,相反,它是一个动态过程,涉及随着时间推移与其他行为者的策略互动。对疫情期间预防行为动态进行定量分析的研究相当匮乏。本文通过建立一个演化博弈论框架来模拟民众采用NPIs的行为动态,填补了这一研究空白。我们构建了两组非对称博弈,其中每组的行为变化由复制方程表征。进行敏感性分析以检验平衡点相对于模型参数扰动的长期稳定性。我们发现,在博弈设定中,民众采用干预措施的极限行为仅由纯策略组成,这表明演化结果是每个人要么采取预防措施,要么不采取。我们还应用该框架来研究戴口罩行为,并用实际数据进行了验证。总体而言,本文为疫情期间采用干预策略的民众动态提供了见解,这有助于政策制定者更好地理解民众行为的演化轨迹。