Using excess deaths and testing statistics to determine COVID-19 mortalities

  1. Lucas Böttcher
  2. Maria R. D’Orsogna
  3. Tom Chou

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Abstract

Factors such as varied definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US from January 2020 until February 2021 is 9 $$\%$$ % higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find statistically insignificant or even negative excess deaths for at least most of 2020 in places such as Germany, Denmark, and Norway.

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  1. Version published to 10.1007/s10654-021-00748-2
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    SciScore for 10.1101/2021.01.10.21249524: (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

    Antibodies
    SentencesResources
    If S, I, R, D are the numbers of susceptible, currently infected, recovered, and deceased individuals, the total population is N = S + I + R + D and the infected fraction can be defined as f = (Nc + Nu)/N = (I + R + D)/N for tests that include recovered and deceased individuals (e.g., antibody tests), or f = (Nc + Nu)/N = (I + D)/N for tests that only count currently infected individuals (e.g., RTPCR tests).
    e.g.
    suggested: None

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    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Strengths and limitations: The proposed use of excess deaths in standard mortality measures may provide more accurate estimates of infection-caused deaths, while errors in the estimates of the fraction of infected individuals in a population from testing can be corrected by estimating the testing bias and testing specificity and sensitivity. One could sharpen estimates of the true COVID-19 deaths by systematically analyzing the statistics of deaths from all reported causes using a standard protocol such as ICD-10 [46]. For example, the mean traffic deaths per month in Spain between 2011-2016 is about 174 persons [47], so any pandemic-related changes to traffic volumes would have little impact considering the much larger number of COVID-19 deaths. Different mortality measures are sensitive to different sources of uncertainty. Under the assumption that all excess deaths are caused by a given infectious disease (e.g., COVID-19), the underlying error in the determined number of excess deaths can be estimated using historical death statistics from the same jurisdiction. Uncertainties in mortality measures can also be decomposed into the uncertainties of their component quantities, including the positive-tested fraction f that depend on uncertainties in the testing parameters. As for all epidemic forecasting and surveillance, our methodology depends on the quality of excess death and COVID-19 case data and knowledge of testing parameters. For many countries, the lack of binding int...

    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.

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  3. Version published to 10.1101/2021.01.10.21249524v1 on medRxiv