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Assessing the Age Specificity of Infection Fatality Rates for COVID-19: Systematic Review, Meta-analysis, & Public Policy Implications

Author

Listed:
  • Andrew T. Levin
  • William P. Hanage
  • Nana Owusu-Boaitey
  • Kensington B. Cochran
  • Seamus P. Walsh
  • Gideon Meyerowitz-Katz

Abstract

To assess age-specific infection fatality rates (IFRs) for COVID-19, we have conducted a systematic review of seroprevalence studies as well as countries with comprehensive tracing programs. Age-specific IFRs were computed using the prevalence data in conjunction with reported fatalities four weeks after the midpoint date of each study, reflecting typical lags in fatalities and reporting. Using metaregression procedures, we find a highly significant log-linear relationship between age and IFR for COVID-19. The estimated age-specific IFRs are very low for children and younger adults but increase progressively to 0.4% at age 55, 1.3% at age 65, 4.2% at age 75, and 14% at age 85. About 90% of the geographical variation in population IFR is explained by differences in age composition of the population and age-specific prevalence. These results indicate that COVID-19 is hazardous not only for the elderly but also for middle-aged adults. Moreover, the population IFR for COVID-19 should not be viewed as a fixed parameter but as intrinsically linked to the age-specific pattern of infections. Consequently, public health measures to protect vulnerable age groups could substantially decrease total deaths.

Suggested Citation

  • Andrew T. Levin & William P. Hanage & Nana Owusu-Boaitey & Kensington B. Cochran & Seamus P. Walsh & Gideon Meyerowitz-Katz, 2020. "Assessing the Age Specificity of Infection Fatality Rates for COVID-19: Systematic Review, Meta-analysis, & Public Policy Implications," NBER Working Papers 27597, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:27597
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    References listed on IDEAS

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    1. Manski, Charles F. & Molinari, Francesca, 2021. "Estimating the COVID-19 infection rate: Anatomy of an inference problem," Journal of Econometrics, Elsevier, vol. 220(1), pages 181-192.
    2. Karl M. Aspelund & Michael C. Droste & James H. Stock & Christopher D. Walker, 2020. "Identification and Estimation of Undetected COVID-19 Cases Using Testing Data from Iceland," NBER Working Papers 27528, National Bureau of Economic Research, Inc.
    3. 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.
    4. Robert E. Hall & Charles I. Jones & Peter J. Klenow, 2020. "Trading Off Consumption and COVID-19 Deaths," Quarterly Review, Federal Reserve Bank of Minneapolis, vol. 42(1), pages 1-14, June.
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    More about this item

    JEL classification:

    • H12 - Public Economics - - Structure and Scope of Government - - - Crisis Management
    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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