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A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing†

A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing† AbstractWe study the optimal lock-down for a planner who controls the fatalities of COVID-19 while minimizing the output costs of the lock-down. The policy prescribes a severe lock-down beginning a few weeks after the outbreak, covering almost 50 percent of the population after a month, with a total duration shy of 4 months. The intensity of the optimal lock-down depends on the gradient of the fatality rate with respect to the infected and the availability of antibody testing, which yields a welfare gain of 2 percent of GDP. We also study test-tracing-quarantine, which we show to be complementary to lock-down. (JEL E23, I12, I15, I18) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Economic Review Insights American Economic Association

A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing†

A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing†

AER: Insights 2021, 3(3): 367–382 https://doi.org/10.1257/aeri.20200201 A Simple Planning Problem for COVID-19 Lock-down, Testing, and Tracing By Fernando Alvarez, David Argente, and Francesco Lippi* We study the optimal lock-down for a planner who controls the fatal- ities of COVID-19 while minimizing the output costs of the lock- down. The policy prescribes a severe lock-down beginning a few weeks after the outbreak, covering almost 50 percent of the popula- tion after a month, with a total duration shy of 4 months. The inten- sity of the optimal lock-down depends on the gradient of the fatality rate with respect to the infected and the availability of antibody testing, which yields a welfare gain of 2 percent of GDP. We also study test-tracing-quarantine, which we show to be complementary to lock-down. (JEL E23, I12, I15, I18) We adopt a variation of the SIR epidemiology model of Kermack and McKendrick (1927) to characterize the optimal policy response to the COVID-19 outbreak under several scenarios. The typical approach in the epidemiology liter - ature is to study the dynamics of the pandemic for infected, deaths, and recovered as functions of some exogenously chosen diffusion parameters, which are in turn related to various policies, such as the partial lock-down of schools, businesses, and other measures of diffusion mitigation, where the diffusion parameters are stratified by individual covariates—see, for example, Ferguson et al. 2020). We ( use a simple version of these models to analyze how to optimally balance the fatalities induced by the epidemic with the output costs of the lock-down pol- icy. Our model thus features a key trade-off between lives saved versus forgone * Alvarez: University of Chicago (email: f-alvarez1@uchicago.edu); Argente: Pennsylvania State University (email: dargente@psu.edu); Lippi: LUISS University (email: francescolippi@gmail.com). Pete Klenow was coeditor for this article. First draft, March 23, 2020. We...
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Publisher
American Economic Association
Copyright
Copyright © 2021 © American Economic Association
ISSN
2640-205X
eISSN
2640-2068
DOI
10.1257/aeri.20200201
Publisher site
See Article on Publisher Site

Abstract

AbstractWe study the optimal lock-down for a planner who controls the fatalities of COVID-19 while minimizing the output costs of the lock-down. The policy prescribes a severe lock-down beginning a few weeks after the outbreak, covering almost 50 percent of the population after a month, with a total duration shy of 4 months. The intensity of the optimal lock-down depends on the gradient of the fatality rate with respect to the infected and the availability of antibody testing, which yields a welfare gain of 2 percent of GDP. We also study test-tracing-quarantine, which we show to be complementary to lock-down. (JEL E23, I12, I15, I18)

Journal

American Economic Review InsightsAmerican Economic Association

Published: Sep 1, 2021

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