COVID-19 mortality, excess mortality, deaths per million and infection fatality ratio, Belgium, 9 March 2020 to 28 June 2020

  1. Geert Molenberghs
  2. Christel Faes
  3. Johan Verbeeck
  4. Patrick Deboosere
  5. Steven Abrams
  6. Lander Willem
  7. Jan Aerts
  8. Heidi Theeten
  9. Brecht Devleesschauwer
  10. Natalia Bustos Sierra
  11. Françoise Renard
  12. Sereina Herzog
  13. Patrick Lusyne
  14. Johan Van der Heyden
  15. Herman Van Oyen
  16. Pierre Van Damme
  17. Niel Hens

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Abstract

COVID-19 mortality, excess mortality, deaths per million population (DPM), infection fatality ratio (IFR) and case fatality ratio (CFR) are reported and compared for many countries globally. These measures may appear objective, however, they should be interpreted with caution.

Aim

We examined reported COVID-19-related mortality in Belgium from 9 March 2020 to 28 June 2020, placing it against the background of excess mortality and compared the DPM and IFR between countries and within subgroups.

Methods

The relation between COVID-19-related mortality and excess mortality was evaluated by comparing COVID-19 mortality and the difference between observed and weekly average predictions of all-cause mortality. DPM were evaluated using demographic data of the Belgian population. The number of infections was estimated by a stochastic compartmental model. The IFR was estimated using a delay distribution between infection and death.

Results

In the study period, 9,621 COVID-19-related deaths were reported, which is close to the excess mortality estimated using weekly averages (8,985 deaths). This translates to 837 DPM and an IFR of 1.5% in the general population. Both DPM and IFR increase with age and are substantially larger in the nursing home population.

Discussion

During the first pandemic wave, Belgium had no discrepancy between COVID-19-related mortality and excess mortality. In light of this close agreement, it is useful to consider the DPM and IFR, which are both age, sex, and nursing home population-dependent. Comparison of COVID-19 mortality between countries should rather be based on excess mortality than on COVID-19-related mortality.

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  1. Version published to 10.2807/1560-7917.es.2022.27.7.2002060
  2. ScreenIT

    SciScore for 10.1101/2020.06.20.20136234: (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
    Statistical software: The data analysis was performed using SAS Software, GAUSS, and R; visualizations were made using Vega.
    Vega
    suggested: (VEGA, RRID:SCR_007907)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

  3. Version published to 10.1101/2020.06.20.20136234v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2020.06.20.20136234: (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
    The data analysis was performed using SAS Software , GAUSS , and R; visualizations were made using Vega .
    Vega
    suggested: (VEGA, SCR_007907)
    Python scripts to reproduce the analyses will be available at https://www.uhasselt.be/DSI.
    Python
    suggested: (IPython, SCR_001658)
    Particular thanks go out to Sciensano colleagues Sara Dequeker and Eline Vandael from the Nursing Homes Competing interest declaration: “All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf ( available on request from the corresponding author ) and declare that ( 1 ) PVD reports research grants from GSK Biologicals , Pfizer , SANOFI , Merck , Themis , Osivax
    GSK Biologicals
    suggested: None
    , J&J and Abbott , grants from The Bill & Melinda Gates Foundation , PATH , Flemish Government , and European Union , outside the submitted work; ( 2 ) none of the other authors has anything to disclose.
    Abbott
    suggested: (Abbott, SCR_010477)
    Quetelet J 2020; 8:7-59. ratio to estimate under-reporting.
    Quetelet J
    suggested: None

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    • Because of its inherent limitations, especially dependence on testing strategy, CFR is a flawed metric for international comparisons

    Results from OddPub: Thank you for sharing your code.

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  5. Version published to 10.1101/2020.06.20.20136234v1 on medRxiv