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

University of Connecticut School of Business Research Paper No. 21-02

Accepted at Manufacturing & Service Operations Management

48 Pages Posted: 14 Jan 2021 Last revised: 22 Feb 2024

See all articles by Miao Bai

Miao Bai

Department of Operations and Information Management, University of Connecticut

Ying Cui

University of California, Berkeley - Department of Industrial Engineering and Operations Research

Guangwen Kong

Temple University-Fox School of Business

Anthony Zhenhuan Zhang

Meta Platforms Inc

Date Written: January 10, 2021

Abstract

Problem definition: Public health interventions such as social distancing and lockdown play an important role in containing infectious disease outbreaks such as COVID-19. Yet, these interventions could cause significant financial losses due to 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 (SIR) disease transmission dynamics. We find that the individual equilibrium activity level is higher than the socially optimal activity level due to 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.

Keywords: COVID-19, dynamic compartmental model, public health policy analysis, game theory

Suggested Citation

Bai, Miao and Cui, Ying and Kong, Guangwen and Zhang, Anthony Zhenhuan, No Panic in Pandemic: The Impact of Individual Choice on Public Health Policy (January 10, 2021). University of Connecticut School of Business Research Paper No. 21-02, Accepted at Manufacturing & Service Operations Management, Available at SSRN: https://ssrn.com/abstract=3763514 or http://dx.doi.org/10.2139/ssrn.3763514

Miao Bai (Contact Author)

Department of Operations and Information Management, University of Connecticut ( email )

OPIM Dept.
2100 Hillside Road, U1041
Storrs, CT CT 06269-1041
United States

Ying Cui

University of California, Berkeley - Department of Industrial Engineering and Operations Research ( email )

4141 Etcheverry Hall
Berkeley, CA 94720-1777
United States

Guangwen Kong

Temple University-Fox School of Business ( email )

531 Alter Hall
1801 Liacouras Walk
Philadephia, PA 19122
United States
19122 (Fax)

HOME PAGE: http://https://www.fox.temple.edu/about-fox/directory/guangwen-kong/

Anthony Zhenhuan Zhang

Meta Platforms Inc ( email )

Menlo Park, CA
United States

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