COVID-19: How Many Years of Life Lost?

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Abstract

Background

COVID-19 was the leading cause of death in the United States over the three-month period March through May 2020. Another perspective is COVID-19’s toll in terms of years of life lost. We calculated years of life lost for COVID-19 and other leading causes of death over those three months in the US. We also predicted years of life lost for COVID-19 and ischemic heart diseases (which includes heart attacks) for March through August 2020.

Methods

Years of life lost are the sum of differences between life expectancy at age of death and age at death. Average years of life lost, years of life lost divided by the number of deaths, were also calculated. We used the COVID-19 Projections Using Machine Learning model to predict years of life lost from COVID-19 through the end of August 2020.

Results

COVID-19 caused 12,035 more deaths than ischemic heart diseases during March through May 2020 but ischemic heart diseases years of life lost were 1.5% greater than those for COVID-19. Average years of life lost were 10.8 and 12.4 for COVID-19 and ischemic heart diseases, respectively. At the end of August, COVID-19 may overtake ischemic heart diseases as the leading cause of deaths and years of life lost in the US.

Conclusion

Each COVID-19 death causes more than a decade of lost life in the US. We are reminded of a Danish Proverb that states “Prediction is difficult, especially when dealing with the future.” We suggest that while dying is bad, losing life is even worse.

Article activity feed

  1. SciScore for 10.1101/2020.06.08.20050559: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    We used Microsoft Excel for all calculations.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    We acknowledge the limitations of this analysis, and hence, will update it in September after the August mortality counts stabilize. We will also include quality of life and comorbidity adjusted YLLs.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.