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The Trade-off Between Prioritization and Vaccination Speed Depends on Mitigation Measures

Author

Listed:
  • Nikhil Agarwal
  • Andrew Komo
  • Chetan A. Patel
  • Parag A. Pathak
  • M. Utku Ünver

Abstract

Calls for eliminating prioritization for SARS-CoV-2 vaccines are growing amid concerns that prioritization reduces vaccination speed. We use an SEIR model to study the effects of vaccination distribution on public health, comparing prioritization policy and speed under mitigation measures that are either eased during the vaccine rollout or sustained through the end of the pandemic period. NASEM's recommended prioritization results in fewer deaths than no prioritization, but does not minimize total deaths. If mitigation measures are eased, abandoning NASEM will result in about 134,000 more deaths at 30 million vaccinations per month. Vaccination speed must be at least 53% higher under no prioritization to avoid increasing deaths. With sustained mitigation, discarding NASEM prioritization will result in 42,000 more deaths, requiring only a 26% increase in speed to hold deaths constant. Therefore, abandoning NASEM's prioritization to increase vaccination speed without substantially increasing deaths may require sustained mitigation.

Suggested Citation

  • Nikhil Agarwal & Andrew Komo & Chetan A. Patel & Parag A. Pathak & M. Utku Ünver, 2021. "The Trade-off Between Prioritization and Vaccination Speed Depends on Mitigation Measures," NBER Working Papers 28519, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28519
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    1. Eric Budish, 2020. "Maximize Utility subject to R≤1: A Simple Price-Theory Approach to Covid-19 Lockdown and Reopening Policy," NBER Working Papers 28093, National Bureau of Economic Research, Inc.
    2. Daron Acemoglu & Victor Chernozhukov & Iván Werning & Michael D. Whinston, 2021. "Optimal Targeted Lockdowns in a Multigroup SIR Model," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 487-502, December.
    3. Amrita Ahuja & Susan Athey & Arthur Baker & Eric Budish & Juan Camilo Castillo & Rachel Glennerster & Scott Duke Kominers & Michael Kremer & Jean Lee & Canice Prendergast & Christopher M. Snyder & Ale, 2021. "Preparing for a Pandemic: Accelerating Vaccine Availability," AEA Papers and Proceedings, American Economic Association, vol. 111, pages 331-335, May.
    4. Colin J. Worby & Hsiao-Han Chang, 2020. "Face mask use in the general population and optimal resource allocation during the COVID-19 pandemic," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    5. repec:rza:wpaper:826 is not listed on IDEAS
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    Cited by:

    1. Anup Malani & Satej Soman & Sabareesh Ramachandran & Alice Chen & Darius N. Lakdawalla, 2022. "Vaccine Allocation Priorities Using Disease Surveillance and Economic Data," NBER Working Papers 29682, National Bureau of Economic Research, Inc.
    2. L'aszl'o Czaller & GergH{o} T'oth & Bal'azs Lengyel, 2021. "Vaccine allocation to blue-collar workers," Papers 2104.04639, arXiv.org.

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    • I1 - Health, Education, and Welfare - - Health

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