Zhou Yuxun, Rahman Mohammad Mafizur, Khanam Rasheda, Taylor Brad R
School of Business, University of Southern Queensland, Toowoomba, Australia.
Appl Math Model. 2023 Oct;122:401-416. doi: 10.1016/j.apm.2023.06.014. Epub 2023 Jun 11.
The ongoing COVID-19 pandemic imposes serious short-term and long-term health costs on populations. Restrictive government policy measures decrease the risks of infection, but produce similarly serious social, mental health, and economic problems. Citizens have varying preferences about the desirability of restrictive policies, and governments are thus forced to navigate this tension in making pandemic policy. This paper analyses the situation facing government using a game-theoretic epidemiological model.
We classify individuals into health-centered individuals and freedom-centered individuals to capture the heterogeneous preferences of citizens. We first use the extended Susceptible-Exposed-Asymptomatic-Infectious-Recovered (SEAIR) model (adding individual preferences) and the signaling game model (adding government) to analyze the strategic situation against the backdrop of a realistic model of COVID-19 infection.
We find the following: 1. There exists two pooling equilibria. When health-centered and freedom-centered individuals send anti-epidemic signals, the government will adopt strict restrictive policies under budget surplus or balance. When health-centered and freedom-centered individuals send freedom signals, the government chooses not to implement restrictive policies. 2. When governments choose not to impose restrictions, the extinction of an epidemic depends on whether it has a high infection transmission rate; when the government chooses to implement non-pharmacological interventions (NPIs), whether an epidemic will disappear depends on how strict the government's restrictions are.
ORIGINALITY/VALUE: Based on the existing literature, we add individual preferences and put the government into the game as a player. Our research extends the current form of combining epidemiology and game theory. By using both we get a more realistic understanding of the spread of the virus and combine that with a richer understanding of the strategic social dynamics enabled by game theoretic analysis. Our findings have important implications for public management and government decision-making in the context of COVID-19 and for potential future public health emergencies.
持续的新冠疫情给民众带来了严重的短期和长期健康代价。政府的限制性政策措施降低了感染风险，但也产生了同样严重的社会、心理健康和经济问题。公民对限制性政策的可取性有不同偏好，因此政府在制定疫情政策时不得不应对这种矛盾。本文使用博弈论流行病学模型分析政府面临的情况。
我们将个体分为以健康为中心的个体和以自由为中心的个体，以体现公民的异质性偏好。我们首先使用扩展的易感-暴露-无症状-感染-康复（SEAIR）模型（加入个体偏好）和信号博弈模型（加入政府），在新冠病毒感染的现实模型背景下分析战略形势。
我们发现以下几点：1. 存在两种混同均衡。当以健康为中心和以自由为中心的个体都发出抗疫信号时，在预算盈余或平衡的情况下，政府将采取严格的限制性政策。当以健康为中心和以自由为中心的个体都发出自由信号时，政府选择不实施限制性政策。2. 当政府选择不实施限制措施时，疫情的消亡取决于其感染传播率是否高；当政府选择实施非药物干预（NPIs）时，疫情是否会消失取决于政府限制措施的严格程度。
原创性/价值：基于现有文献，我们加入了个体偏好，并将政府作为参与者纳入博弈。我们的研究扩展了当前流行病学与博弈论相结合的形式。通过同时使用这两种方法，我们对病毒传播有了更现实的理解，并将其与通过博弈论分析对战略社会动态的更丰富理解相结合。我们的研究结果对新冠疫情背景下的公共管理和政府决策以及未来潜在的公共卫生紧急情况具有重要意义。
