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Measuring Deaths from COVID-19

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  • Dionissi Aliprantis
  • Kristen Tauber

Abstract

Medical data are new to the analyses and deliberations of Federal Reserve monetary policymakers, but such data are now of primary importance to policymakers who need to understand the virus’s trajectory to assess economic conditions and address the virus’s impacts on the economy. The number of deaths caused by COVID-19 is one key metric that is often referred to, but as with other COVID metrics, it is a challenge to measure accurately. We discuss the issues involved in measuring COVID-19 deaths and argue that the change in the number of directly observed COVID-19 deaths is the most reliable and timely approach when using deaths to judge the trajectory of the pandemic in the United States, which is critical given the current inconsistencies in testing and limitations of hospitalization data.

Suggested Citation

  • Dionissi Aliprantis & Kristen Tauber, 2020. "Measuring Deaths from COVID-19," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2020(18), pages 1-7, July.
    • Handle: RePEc:fip:fedcec:88336
    DOI: 10.26509/frbc-ec-202018
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    References listed on IDEAS

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    1. V. V. Chari & Rishabh Kirpalani & Christopher Phelan, 2021. "The Hammer and the Scalpel: On the Economics of Indiscriminate versus Targeted Isolation Policies during Pandemics," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 42, pages 1-14, October.
    2. Charles F. Manski, 2015. "Communicating Uncertainty in Official Economic Statistics: An Appraisal Fifty Years after Morgenstern," Journal of Economic Literature, American Economic Association, vol. 53(3), pages 631-653, September.
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    Cited by:

    1. Alexander Dietrich & Edward S. Knotek & Michael McMain & Kristian Ove R. Myrseth & Raphael Schoenle & Michael Weber, 2021. "Expected Post-Pandemic Consumption and Scarred Expectations from COVID-19," Economic Commentary, Federal Reserve Bank of Cleveland, vol. 2021(11), pages 1-8, April.
    2. Kunz, Johannes & Propper, Carol, 2022. "Is Hospital Quality Predictive of Pandemic Deaths? Evidence from US Counties," CEPR Discussion Papers 17365, C.E.P.R. Discussion Papers.
    3. Fuyu Xu & Kate Beard, 2021. "A comparison of prospective space-time scan statistics and spatiotemporal event sequence based clustering for COVID-19 surveillance," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-23, June.
    4. Kunz, Johannes S. & Propper, Carol, 2023. "JUE Insight: Is hospital quality predictive of pandemic deaths? Evidence from US counties," Journal of Urban Economics, Elsevier, vol. 133(C).

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