The Social-Economic-Epidemiological Choice: Incorporating Human Response and Avoiding Policy Mistakes was presented at the ASSA Conference, NAFE virtual sessions in January 2021. The paper provides “evidence that decisions made using a sequential decision model can preserve public health better than those that rely upon naïve, passive epidemiological models.”
The Costs and Consequences of the Coronavirus Pandemic: Three Lessons was presented virtually in June 2020 for the Western Economics Association. This presentation describes three critical lessons regarding the use of empirical models and governmental efforts to contain the outbreak.
The pandemic of 2020 appeared to present a stark choice: either harshly restrict travel, socialization, and work in the manner of the quaranta giorni of the Middle Ages at enormous economic cost; or relax such restrictions and accept a surge in the number of people infected and the possibility of overwhelming the medical infrastructure.
This choice was commonly presented as a rigid “doomsday dichotomy:” either protect public health by shutting down schools, businesses, and events; or let people sicken and die. A critical basis for this dichotomy was the use of passive epidemiological models, built largely on the same framework as the SIR model first introduced in 1927. These models often carried embedded assumptions that enforced this dichotomy, such as the notion that health care system resources were fixed, human behavior was largely determined by government policy, treatment options would not improve over time, and government restrictions were costless and always beneficial to public health. Within this structure, passive epidemiological models such as the classic SIR model became the dominant mode of thinking about policy options in a pandemic.
In fact, government restrictions have both positive and negative consequences for public health. Individual behavior is affected, but not dictated by, governments. Multiple policy options existed. Uncertainty was profound, especially in the early months of the pandemic. As a result, the “doomsday dichotomy” was false, and the usefulness of passive epidemiological models must be questioned.
We identify at least two classes of sequential decision models that address the serious deficiencies identified above. First, we recommend the “behavioral SIR” models that build upon classic epidemiological models but directly incorporate human choice. Second, we propose a novel social-economic-epidemiological choice model where: (1) people make decisions under conditions of uncertainty, (2) policy options include pursuit of vaccination and local mitigation, and (3) public health costs of restrictions are directly considered. We provide evidence that decisions made using a sequential decision model can preserve public health better than those that rely upon naïve, passive epidemiological models.