Evidence map›Paper›PMID 32894287›Full record

ArticleJournal of public health (Oxford, England)2020

Years of life lost associated with COVID-19 deaths in the United States.

Troy Quast, Ross Andel, Sean Gregory, Eric A Storch

Abstract read
In one paragraph

Article in Journal of public health (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

  1. Article
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  5. Impact of COVID-19 on Spanish mortality rates in 2020 by age and sex.Journal of public health (Oxford, England) · 2023
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  6. Article
  7. Article
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  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Excess mortality from COVID and non-COVID causes in minority populations.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  15. Article
  16. Article
  17. Article
  18. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Troy QuastUniversity of South Florida, College of Public Health, Tampa, FL 33612, USA.
Ross AndelUniversity of South Florida, College of Behavioral and Community Sciences, Tampa, FL 33620, USA.
Sean GregoryDepartment of Politics and International Affairs, Northern Arizona University, Flagstaff, AZ 86011, USA.
Eric A StorchMenninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe mortality effects of COVID-19 are a critical aspect of the disease's impact. Years of life lost (YLLs) can provide greater insight than the number of deaths by conveying the shortfall in life expectancy and thus the age profile of the decedents.

methodsWe employed data regarding COVID-19 deaths in the USA by jurisdiction, gender and age group for the period 1 February 2020 through 11 July 2020. We used actuarial life expectancy tables by gender and age to estimate YLLs.

resultsWe estimated roughly 1.2 million YLLs due to COVID-19 deaths. The YLLs for the top six jurisdictions exceeded those for the remaining 43. On a per-capita basis, female YLLs were generally higher than male YLLs throughout the country.

conclusionsOur estimates offer new insight into the effects of COVID-19. Our findings of heterogenous rates of YLLs by geography and gender highlight variation in the magnitude of the pandemic's effects that may inform effective policy responses.

Indexed as

Life ExpectancyActuarial AnalysisAge FactorsCOVID-19FemaleHumansMalePandemicsSARS-CoV-2Sex FactorsUnited StatesCOVID-19mortalityyears of lost life

Identifiers

PMID32894287
PMCPMC7499646

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.