A Simple Planning Problem for COVID-19 Lockdown

Fernando Alvarez () and David Argente
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Fernando Alvarez: University of Chicago - Booth School of Business and NBER

No 2020-34, Working Papers from Becker Friedman Institute for Research In Economics

Abstract: We study the optimal lockdown policy for a planner who controls the fatalities of a pandemic while minimizing the output costs of the lockdown. The policy depends on the fraction of infected and susceptible in the population, prescribing a severe lockdown beginning two weeks after the outbreak, covering 60% of the population after a month, and gradually withdrawing to 20% of the population after 3 months. The intensity of the optimal lockdown depends on the gradient of the fatality rate with respect to the infected, and the availability of antibody testing that yields a welfare gain of 2% of GDP.

Keywords: Dynamic programming; epidemic control; lockdown; Quarantine (search for similar items in EconPapers)
JEL-codes: C61 I10 I18 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2020
New Economics Papers: this item is included in nep-hea
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https://repec.bfi.uchicago.edu/RePEc/pdfs/BFI_WP_202034.pdf (application/pdf)

Related works:
Working Paper: A Simple Planning Problem for COVID-19 Lockdown (2020)
Working Paper: A Simple Planning Problem forCOVID-19 Lockdown (2020)
Working Paper: A Simple Planning Problem for COVID-19 Lockdown (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:bfi:wpaper:2020-34

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