No Panic in Pandemic: The Impact of Individual Choice on Public Health Policy

• 成果类型: Article
• 署名作者: Bai, Miao; Cui, Ying; Kong, Guangwen; Zhang, Anthony Zhenhuan
• 署名单位: University of Connecticut; University of California System; University of California Berkeley; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
• 刊物名称: M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1523-4614
• DOI: 10.1287/msom.2022.0514
• 发表日期: 2024
• 页码: 1622-1638
• 关键词: covid-19; dynamic compartmental model; public health policy analysis; game theory; logit model

摘要

Problem definition: Public health interventions, such as social distancing and lockdown, play an important role in containing infectious disease outbreaks, such as coronavirus disease 2019 (COVID-19). Yet, these interventions could cause significant financial losses because of the disruption to regular socioeconomic activities. Moreover, an individual's activity level is influenced not only by public health policies but also by one's perception of the disease burden of infection. Strategic planning is required to optimize the timing and intensity of these public health interventions by considering individual responses. Methodology/results: We use the multinomial logit choice model to characterize individual reactions to the risk of infection and public health interventions and integrate it into a repeated Stackelberg game with the susceptible -infected -recovered disease transmission dynamics. We find that the individual equilibrium activity level is higher than the socially optimal activity level because of an individual's ignorance of the negative externality imposed on others. As a result, implementing lockdown and social distancing policies at moderate disease prevalence may be equivalently critical, if not more, compared with their implementations when the disease prevalence is at its peak level. To verify these findings, we conduct numerical studies based on representative COVID-19 data in Minnesota. Managerial implications: Our results call for policymakers' attention to consider the impact of individuals' responses in the planning for different pandemic containment measures. Individuals' responses in the pandemic may significantly affect the optimal implementation of lockdown and social distancing policies.