Optimal social distancing and the economics of uncertain vaccine arrival

Abstract

We analytically identify two mechanisms that explain why a later arrival time for a pandemic-ending vaccine has an ambiguous effect on optimal social-distancing policy. We assess the net effect of these channels using a quantitative model solved for over a thousand parameter combinations. Optimal policy and welfare comparisons are both highly sensitive to beliefs about vaccine arrival. A policy of moving quickly to herd immunity by requiring social distancing for only the most vulnerable might be loosely justified for expected vaccine arrivals over 2 years, but becomes catastrophic if the expected arrival is within a year. | INTRODUCTIONExpectations about the time needed to develop and distribute a COVID-19 vaccine evolved quickly during the first year of the pandemic. An informal survey of experts from February 2020 concluded that developing, licensing, and manufacturing a vaccine within 12 months would be remarkable, even revolutionary (Kormann, 2020). In July, a formal expert elicitation put September 2021 as the best guess for widespread public access (Kane et al., 2020). Many also recognized that a vaccine might prove elusive, as it has for other important diseases, such as AIDS and the common cold. In the end, the vaccine arrived faster than expected, with Britain becoming the first Organisation for Economic Cooperation and Development country to approve a vaccine on December 3, 2020.At least since Yaari (1965), economists have understood the relation between discounting and the expected time of an event that ends a problem: death in Yaari's setting and vaccine arrival in the epidemic context. Earlier expected arrival makes the future less extensive and therefore less important, having qualitatively the same effect on optimal planning as a higher discount rate. Nevertheless, the impact of vaccine arrival in a Susceptible-Infected-Removed

Vaccination under pessimistic expectations in clinical trials and immunization campaigns

“…Last but not least, this paper complements other frameworks that have e.g. studied the political economy of vaccination (Iverson, Karp, & Peri, 2022;Manski, 2017;Nganmeni, Pongou, Tchantcho, & Tondji, 2022). Our model is used to illustrate the vaccination episode of the COVID-19 pandemic but do not consider other preventive behaviors such that antibody testing (Guimarães, 2021) or self-isolation (Baril-Tremblay, Marlats, & Ménager, 2021).…”

Introduction to the special issue on new insights into economic epidemiology: Theory and policy

“…This section considers two of them. The first, specific to the COVID crisis, studies the impact of uncertainty around vaccine-arrival time on the optimal design of NPIs, here social-distancing policy (Iverson et al, 2022). The same question has been recently tackled by Federico and Ferrari (2021) in a stochastic SIR model, assuming vaccination is discovered at a random time, exponentially distributed.…”

“…Using a dynamic programming model with a stochastic vaccine-arrival time and a quantitative SIR model, Iverson et al (2022) analytically identify two mechanisms that explain why a later arrival time for a pandemic-ending vaccine has an ambiguous effect on optimal social-distancing policy. The functional form of beliefs has only a small effect on optimal policy, but the expected vaccine-arrival time has a large effect.…”

“…The same question has been recently tackled by Federico and Ferrari (2021) in a stochastic SIR model, assuming vaccination is discovered at a random time, exponentially distributed. However, while the latter paper solves a central planner problem, Iverson et al (2022) look at the deep microfoundations of the problem. The second paper is a novel political economygrounded approach to the social acceptability of vaccination by Nganmeni et al (2022), another very important issue worldwide.…”

First‐best health policy in vaccine markets with health and network externalities

“…See, for example,Adida et al (2012) andIverson et al (2022) for more on the role of random production timing. 5 Interestingly, while the externality at hand is a positive one in the context of the strategic vaccine game in that every individual benefits from a person's decision to vaccinate, it becomes a negative network externality on the resulting demand, as it leads to its contraction.…”