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

To put estimates of COVID-19 mortality into perspective, we estimate age-specific mortality for an epidemic claiming for illustrative purposes 1 million US lives, with results approximately scalable over a broad range of deaths. We calculate the impact on period life expectancy (down 2.94 y) and rem...

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Autores principales: Goldstein, Joshua R., Lee, Ronald D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486771/
https://www.ncbi.nlm.nih.gov/pubmed/32820077
http://dx.doi.org/10.1073/pnas.2006392117
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author Goldstein, Joshua R.
Lee, Ronald D.
author_facet Goldstein, Joshua R.
Lee, Ronald D.
author_sort Goldstein, Joshua R.
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description To put estimates of COVID-19 mortality into perspective, we estimate age-specific mortality for an epidemic claiming for illustrative purposes 1 million US lives, with results approximately scalable over a broad range of deaths. We calculate the impact on period life expectancy (down 2.94 y) and remaining life years (11.7 y per death). Avoiding 1.75 million deaths or 20.5 trillion person years of life lost would be valued at $10.2 to $17.5 trillion. The age patterns of COVID-19 mortality in other countries are quite similar and increase at rates close to each country’s rate for all-cause mortality. The scenario of 1 million COVID-19 deaths is similar in scale to that of the decades-long HIV/AIDS and opioid-overdose epidemics but considerably smaller than that of the Spanish flu of 1918. Unlike HIV/AIDS and opioid epidemics, the COVID-19 deaths are concentrated in a period of months rather than spread out over decades.
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spelling pubmed-74867712020-09-23 Demographic perspectives on the mortality of COVID-19 and other epidemics Goldstein, Joshua R. Lee, Ronald D. Proc Natl Acad Sci U S A Social Sciences To put estimates of COVID-19 mortality into perspective, we estimate age-specific mortality for an epidemic claiming for illustrative purposes 1 million US lives, with results approximately scalable over a broad range of deaths. We calculate the impact on period life expectancy (down 2.94 y) and remaining life years (11.7 y per death). Avoiding 1.75 million deaths or 20.5 trillion person years of life lost would be valued at $10.2 to $17.5 trillion. The age patterns of COVID-19 mortality in other countries are quite similar and increase at rates close to each country’s rate for all-cause mortality. The scenario of 1 million COVID-19 deaths is similar in scale to that of the decades-long HIV/AIDS and opioid-overdose epidemics but considerably smaller than that of the Spanish flu of 1918. Unlike HIV/AIDS and opioid epidemics, the COVID-19 deaths are concentrated in a period of months rather than spread out over decades. National Academy of Sciences 2020-09-08 2020-08-20 /pmc/articles/PMC7486771/ /pubmed/32820077 http://dx.doi.org/10.1073/pnas.2006392117 Text en Copyright © 2020 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/ https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
Goldstein, Joshua R.
Lee, Ronald D.
Demographic perspectives on the mortality of COVID-19 and other epidemics
title Demographic perspectives on the mortality of COVID-19 and other epidemics
title_full Demographic perspectives on the mortality of COVID-19 and other epidemics
title_fullStr Demographic perspectives on the mortality of COVID-19 and other epidemics
title_full_unstemmed Demographic perspectives on the mortality of COVID-19 and other epidemics
title_short Demographic perspectives on the mortality of COVID-19 and other epidemics
title_sort demographic perspectives on the mortality of covid-19 and other epidemics
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7486771/
https://www.ncbi.nlm.nih.gov/pubmed/32820077
http://dx.doi.org/10.1073/pnas.2006392117
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