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Optimal Case Detection and Social Distancing Policies to Suppress COVID-19

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  • Pollinger, Stefan

Abstract

This paper shows that the optimal combination of social distancing and case detection allows for complete and efficient eradication of COVID-19. The first contribution is theoretical. I show that the optimal suppression-policy is a simple function of observable sufficient-statistics, making it easily implementable. I prove that optimal social distancing is the strongest when an outbreak is detected, and then gradually relaxed. If case detection is sufficiently efficient, social distancing vanishes wholly and quickly; otherwise, it needs to stay in place until a vaccine arrives. The second contribution is quantitative. I find that, if Italy adopts digital contact tracing, total suppression costs only 0.8% of annual GDP. In sharp contrast, under the current detection efficiency, the total cost of suppression amounts to at least 14% of GDP.

Suggested Citation

  • Pollinger, Stefan, 2020. "Optimal Case Detection and Social Distancing Policies to Suppress COVID-19," TSE Working Papers 20-1109, Toulouse School of Economics (TSE).
    • Handle: RePEc:tse:wpaper:124343
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    References listed on IDEAS

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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Distancing and Lockdown > Optimal policy
    2. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Health > Tracing

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    Cited by:

    1. Christian Gollier, 2020. "Pandemic economics: optimal dynamic confinement under uncertainty and learning," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 45(2), pages 80-93, September.
    2. Miclo, Laurent & Spiro, Daniel & Weibull, Jörgen, 2022. "Optimal epidemic suppression under an ICU constraint: An analytical solution," Journal of Mathematical Economics, Elsevier, vol. 101(C).
    3. Acedański, Jan, 2021. "Optimal lockdown policy during the election period," Economic Analysis and Policy, Elsevier, vol. 72(C), pages 102-117.
    4. Łukasz Rachel, 2020. "An Analytical Model of Covid-19 Lockdowns," Discussion Papers 2029, Centre for Macroeconomics (CFM).
    5. Yoshiro Tsutsui & Shosh Shahrabani & Eiji Yamamura & Ryohei Hayashi & Youki Kohsaka & Fumio Ohtake, 2021. "The Willingness to Pay for a Hypothetical Vaccine for the Coronavirus Disease 2019 (COVID-19)," IJERPH, MDPI, vol. 18(23), pages 1-16, November.

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