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Cited by 287Insurance, Mortality, Demography, Risk ManagementCOVID-19 epidemiological studiesHealthcare Systems and Public Health

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Demographic perspectives on the mortality of COVID-19 and other epidemics

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Goldstein, Joshua R., Lee, Ronald D.·2020·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.2006392117PMC PMC7486771
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Abstract

Significance: What would a hypothetical 1 million US deaths in the COVID-19 epidemic mean for mortality of individuals at the population level? Life expectancy for 2020 would drop by 2.9 y. Those dying would lose an average of 11.7 y of expected remaining life, while for the general population the loss of remaining life would be 0.2 y for elders (at age 80) and much less at younger ages. Mortality per person would be less than that of the Spanish flu, but closer to that of the opioid and HIV/AIDS epidemics, while far more concentrated in time. The standard valuation of averting 1.75 million deaths would be many trillions of dollars.

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Fig. 1. Similar age pattern of COVID-19 mortality by region. (A) Unnormalized age-specific mortality, calculated as the ratio of deaths by age to population by age. The levels should not be interpreted as reflecting real differences in mortality because of unaccounted variation in time scale, stage of the epidemic, and the extent of spread within the region. (B) Normalized rates, dividing each region’s rates by the sum of these rates, allow comparison of the age pattern. The average is calculated across all regions. Exponential increase at a rate of 0.11 is plotted to intersect the average in the age group 70 to 79 y. A and B, Lower show the same data as A and B, Upper but in logarithmic scale. (For sources, see main text Epidemic Mortality Risk as Temporary Aging.)
Fig. 1. Similar age pattern of COVID-19 mortality by region. (A) Unnormalized age-specific mortality, calculated as the ratio of deaths by age to population by age. The levels should not be interpreted as reflecting real differences in mortality because of unaccounted variation in time scale, stage of the epidemic, and the extent of spread within the region. (B) Normalized rates, dividing each region’s rates by the sum of these rates, allow comparison of the age pattern. The average is calculated across all regions. Exponential increase at a rate of 0.11 is plotted to intersect the average in the age group 70 to 79 y. A and B, Lower show the same data as A and B, Upper but in logarithmic scale. (For sources, see main text Epidemic Mortality Risk as Temporary Aging.)CC BY-NC-ND · PubMed Central
Fig. 2. The relationship between exponential rates of increase with age of all-cause mortality and COVID-19 mortality for countries in the Human Mortality Database. (Note that exponential rates are calculated from age groups 45 to 49 y to 85 to 89 y for all-cause mortality and ages 40 to 49 y to 80+ y for COVID-19 mortality, assuming 40-y ranges for both.)
Fig. 2. The relationship between exponential rates of increase with age of all-cause mortality and COVID-19 mortality for countries in the Human Mortality Database. (Note that exponential rates are calculated from age groups 45 to 49 y to 85 to 89 y for all-cause mortality and ages 40 to 49 y to 80+ y for COVID-19 mortality, assuming 40-y ranges for both.)CC BY-NC-ND · PubMed Central
Fig. 3. Estimated age-specific mortality in the United States in 2020 for the scenario of 1 million additional COVID-19 deaths. Baseline mortality in 2020 is assumed to equal that in 2017. COVID-19 mortality is estimated by averaging the normalized death rates in Fig. 1B and then multiplying these average rates to result in 1 million additional deaths using the US population age structure for 2020.
Fig. 3. Estimated age-specific mortality in the United States in 2020 for the scenario of 1 million additional COVID-19 deaths. Baseline mortality in 2020 is assumed to equal that in 2017. COVID-19 mortality is estimated by averaging the normalized death rates in Fig. 1B and then multiplying these average rates to result in 1 million additional deaths using the US population age structure for 2020.CC BY-NC-ND · PubMed Central
Fig. 4. Mortality of COVID-19 scenario compared to past US epidemics according to different measures. In the scenario of 1 million COVID-19 deaths, the virus kills more Americans than past epidemics, but when population size is accounted for, Spanish flu is more deadly. Taking into account years of remaining life, we calculate that the Spanish flu resulted in even larger losses. The scales of the HIV and opioid epidemics were much smaller each year, but over decades became comparable to COVID-10 in terms of per-capita deaths and to Spanish flu in terms of life years lost. The scenario of 250,000 COVID-19 deaths is also shown with a dashed line. (Source: our calculations detailed in Materials and Methods.)
Fig. 4. Mortality of COVID-19 scenario compared to past US epidemics according to different measures. In the scenario of 1 million COVID-19 deaths, the virus kills more Americans than past epidemics, but when population size is accounted for, Spanish flu is more deadly. Taking into account years of remaining life, we calculate that the Spanish flu resulted in even larger losses. The scales of the HIV and opioid epidemics were much smaller each year, but over decades became comparable to COVID-10 in terms of per-capita deaths and to Spanish flu in terms of life years lost. The scenario of 250,000 COVID-19 deaths is also shown with a dashed line. (Source: our calculations detailed in Materials and Methods.)CC BY-NC-ND · PubMed Central

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  1. Institute for Clinical and Economic Review 2020-2023 value assessment framework. https://icer-review.org/wp-content/uploads/2019/05/ICER_2020_2023_VAF_013120-4.pdf. Accessed 31 March 2020.

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Metadata

Authors
Goldstein, J. R., & Lee, R. D.
Affiliations
University of California, Berkeley (US)
Corresponding author
  • Goldstein, Joshua R.
  • Lee, Ronald D.
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2020-08-20
Volume
117
Issue
36
Pages
22035-22041
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.2006392117
PMC
PMC7486771
OpenAlex
W3017550043
Cited by
287
References
16
Citations by year
2026: 8 · 2025: 25 · 2024: 29 · 2023: 38 · 2022: 71 · 2021: 94 · 2020: 22
FWCI
84.79
Type
journal article
Language
en
Update notices
correction (2020-11-02)
Open access
Licence
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
Funders
  • HHS | NIH | National Institute on Aging (5P30AG012839, R01AG058940)
  • HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development (P2CHD072964)
Topics
  • Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Health Sciences › Medicine › Epidemiology › Healthcare Systems and Public Health
Keywords
COVID-19 mortality, age-specific mortality, period life expectancy, years of life lost, HIV/AIDS epidemic, opioid overdose epidemic, 1918 influenza pandemic, all-cause mortality
MeSH terms
Betacoronavirus, COVID-19, SARS-CoV-2, Demography, Humans, Life Expectancy, Mortality, Pneumonia, Viral, United States, Cost of Illness, Coronavirus Infections, History, 20th Century, History, 21st Century, Epidemics, Pandemics

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