## Assessing Targeted Containment Policies to Fight COVID-19

_IMF Working Papers, December 11, 2020_

## Source details

**Canonical URL:** [Assessing Targeted Containment Policies to Fight COVID-19](https://www.imf.org/en/publications/wp/issues/2020/12/11/assessing-targeted-containment-policies-to-fight-covid-19-49878)

## Other formats

- [Markdown version](/en/publications/wp/issues/2020/12/11/assessing-targeted-containment-policies-to-fight-covid-19-49878/index.md)
- [Structured JSON version](/en/publications/wp/issues/2020/12/11/assessing-targeted-containment-policies-to-fight-covid-19-49878/index.json)
- [Bundle manifest](/en/publications/wp/issues/2020/12/11/assessing-targeted-containment-policies-to-fight-covid-19-49878/bundle-manifest.json)

## Bibliographic details
- Authors: Francesco Grigoli, José M. Mota
- Published: December 11, 2020
- Series: IMF Working Papers
- DOI: https://doi.org/10.5089/9781513560915.001

---

### Summary
- The paper assesses targeted containment as an alternative to non-discriminatory (blanket) lockdowns in response to COVID-19 outbreaks.
- It develops a SIR-macro model with heterogeneous agents by mortality rates and contact rates, where the government optimally bans people from working.
- Core tradeoff: targeted containment reduces deaths relative to blanket policies but leads to a larger and longer recession because containment applies to a larger fraction of people, is held for longer, and delays herd immunity.
- Increased interactions between low- and high-risk individuals reduce the effectiveness of targeted containment.

### Model and Methodology
- Model type: SIR-macro model incorporating heterogeneous agents in mortality rates and contact rates.
- Government policy instrument: optimal bans on working for portions of the population.
- Behavioral feature considered: voluntary social distancing (mentioned as a keyword).

### Main Findings
- Under a targeted policy, the optimal containment:
  - Reaches a larger portion of the population than under a blanket policy.
  - Is held in place for longer than under a blanket policy.
- Health outcome:
  - A targeted approach results in a smaller death count compared to a blanket policy.
- Economic outcome:
  - The recession is larger under a targeted approach than under a blanket policy.
  - Reasons: containment applies to a larger fraction of people, remains in place longer, and herd immunity is achieved later.
- Interaction effects:
  - Increased interactions between low- and high-risk individuals effectively reduce the benefits of a targeted approach.

### Policy Implications
- Targeted containment can reduce mortality but at the cost of deeper and more prolonged economic contraction.
- Policymakers should consider the degree of interaction between risk groups when evaluating targeted containment, as high interaction undermines benefits.
- Optimal policy design must balance mortality reduction against larger recessionary effects and delayed herd immunity.

---

## Content in this bundle

- **Working Paper**
  - [Working Paper (Markdown version)](/-/media/files/publications/wp/2020/english/wpiea2020277-print-pdf.pdf.md){rel="alternate" type="text/markdown"}
  - [Working Paper (PDF)](/-/media/files/publications/wp/2020/english/wpiea2020277-print-pdf.pdf){rel="external" type="application/pdf"}

---

_Source: https://www.imf.org/en/publications/wp/issues/2020/12/11/assessing-targeted-containment-policies-to-fight-covid-19-49878_