No Panic in Pandemic: The Impact of Individual Choice on Public Health Policy and Vaccine Priority
60 Pages Posted: 14 Jan 2021 Last revised: 20 Feb 2021
Date Written: January 10, 2021
Infectious disease outbreaks such as the COVID-19 pandemic pose significant public health threats and challenges worldwide because of the high transmissibility and potentially severe symptoms and complications if infected. Although public health interventions such as social distancing and lockdown can slow down the disease spread, they may cause a significant financial loss due to their disruption to regular economic and social activities. Strategic planning of public health interventions is required to optimize the timing and intensity of these interventions by considering human responses to those public health policies. To optimize public health interventions, we use a multinomial discrete choice model to characterize individual activity level and integrate it into a repeated game-theoretical model with epidemiological compartmental models capturing disease transmission dynamics. We derive insightful structural properties from these models and conduct numerical studies based on representative COVID-19 data in Minnesota. 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, with the largest difference at a middle-range disease prevalence. As a result, counter to the intuition that lockdown policy should be instituted when the disease prevalence is at its peak level, we find that the lockdown policy is more effective when the disease prevalence is moderate. Similarly, social distancing policy should be more emphasized after the disease prevalence peak and is necessary even when vaccines become available. We also find that social distancing is more effective than lockdown based on the representative COVID-19 data in Minnesota. Lastly, we find that the trade-off between higher mortality rate and negative externality imposed by the active age/risk group is the key to determine the best strategy for vaccination priority. The change of vaccine capacity, mortality rate, and contract transmission rate would result in different vaccination priorities.
Keywords: COVID-19, dynamic compartmental model, public health policy analysis, game theory, multinomial logit model
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