Stay Home or Not? Modeling Individuals’ Decisions During the COVID-19 Pandemic

IF 2.5 4区 管理学 Q3 MANAGEMENT Decision Analysis Pub Date : 2021-09-07 DOI:10.1287/deca.2021.0437
Qifeng Wan, Xuan-hua Xu, Kyle Hunt, J. Zhuang
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引用次数: 5

Abstract

During the COVID-19 pandemic, staying home proved to be an effective way to mitigate the spread of the virus. Stay-at-home orders and guidelines were issued by governments across the globe and were followed by a large portion of the population in the early stages of the outbreak when there was a lack of COVID-specific medical knowledge. The decision of whether to stay home came with many trade-offs, such as risking personal exposure to the virus when leaving home or facing financial and mental health burdens when remaining home. In this research, we study how individuals make strategic decisions to balance these conflicting outcomes. We present a model to study individuals’ decision making based on decision and prospect theory, and we conduct sensitivity analysis to study the fluctuations in optimal strategies when there are changes made to the model’s parameters. A Monte Carlo simulation is implemented to further study the performance of our model, and we compare our simulation results with real data that captures individuals’ stay-at-home decisions. Overall, this research models and analyzes the behaviors of individuals during the COVID-19 pandemic and can help support decision making regarding control measures and policy development when public health emergencies appear in the future.
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呆在家里还是不呆?COVID-19大流行期间个人决策建模
在2019冠状病毒病大流行期间,待在家里被证明是缓解病毒传播的有效方法。全球各国政府发布了居家令和指导方针,在疫情爆发的早期阶段,由于缺乏针对covid - 19的医学知识,很大一部分人都遵循了这些命令和指导方针。是否留在家里的决定需要做出许多权衡,例如离开家时可能会有个人接触病毒的风险,或者留在家里时面临经济和精神健康负担。在这项研究中,我们研究个人如何做出战略决策来平衡这些冲突的结果。基于决策与前景理论,建立了个体决策模型,并对模型参数变化时最优策略的波动进行了敏感性分析。为了进一步研究模型的性能,我们实施了蒙特卡罗模拟,并将模拟结果与捕获个人在家决策的真实数据进行了比较。总体而言,本研究对COVID-19大流行期间的个人行为进行了建模和分析,可以为未来出现突发公共卫生事件时的控制措施和政策制定决策提供支持。
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来源期刊
Decision Analysis
Decision Analysis MANAGEMENT-
CiteScore
3.10
自引率
21.10%
发文量
19
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