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Assessing Targeted Containment Policies to Fight COVID-19

Author

Listed:
  • Checo, Ariadne
  • Grigoli, Francesco
  • Mota, Jose M.

Abstract

The large economic costs of full-blown lockdowns in response to COVID-19 outbreaks, coupled with heterogeneous mortality rates across age groups, led to question non-discriminatory containment mea- sures. In this paper we provide an assessment of the targeted approach to containment. We propose a SIR-macro model that allows for heterogeneous agents in terms of mortality rates and contact rates, and in which the government optimally bans people from working. We find that under a targeted pol- icy, the optimal containment reaches a larger portion of the population than under a blanket policy and is held in place for longer. Compared to a blanket policy, a targeted approach results in a smaller death count. Yet, it is not a panacea: the recession is larger under such approach as the containment policy applies to a larger fraction of people, remains in place for longer, and herd immunity is achieved later. Moreover, we find that increased interactions between low- and high-risk individuals effectively reduce the benefits of a targeted approach to containment.

Suggested Citation

  • Checo, Ariadne & Grigoli, Francesco & Mota, Jose M., 2021. "Assessing Targeted Containment Policies to Fight COVID-19," GLO Discussion Paper Series 752, Global Labor Organization (GLO).
  • Handle: RePEc:zbw:glodps:752
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    More about this item

    Keywords

    Optimal containment policies; COVID-19; heterogeneous agents; mortality rate; voluntary social distancing;
    All these keywords.

    JEL classification:

    • E10 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - General
    • H00 - Public Economics - - General - - - General
    • I10 - Health, Education, and Welfare - - Health - - - General

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