Assessing Targeted Containment Policies to Fight COVID-19

By Ariadne Checo, Francesco Grigoli, José M. Mota

December 11, 2020

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Ariadne Checo, Francesco Grigoli, and José M. Mota Assessing Targeted Containment Policies to Fight COVID-19, (USA: International Monetary Fund, 2020) accessed November 21, 2024

Disclaimer: IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, or IMF management.

Summary

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 measures. 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 policy, 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.

Subject: Aging, Consumption, Health, Labor, Population and demographics

Keywords: Blanket policy scenario, Containment policy, COVID-19, Heterogeneous agents, Optimal containment, Optimal containment policies, Policy scenario, Recession, Share of contact, Targeted policy approach, Voluntary social distancing., WP

Publication Details

Pages:

31
Volume:

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DOI:

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Issue:

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Series:

Working Paper No. 2020/277
Stock No:

WPIEA2020277
ISBN:

9781513560915
ISSN:

1018-5941

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