The role of population structure when measuring COVID-19 impact across countries

  1. Octavio Bramajo
  2. Mauro Infantino
  3. Rafael Unda
  4. Walter D Cardona-Maya
  5. Pablo Richly

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Abstract

The search for accurate indicators to compare the pandemic impact between countries is still a challenge. The crude death rate, case fatality rate by country and sex, standardized fatality rate, and standardized death rate were calculated using data from Argentina and Colombia countries. We show that even when frequently used indicator as deaths per million are quite similar, 512 deaths per million in Argentina and 522 deaths per million in Colombia, a significant heterogeneity can be found when the mortality data is decomposed by sex or age.

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  1. ScreenIT

    SciScore for 10.1101/2020.11.30.20239947: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIACUC: Given that the data were anonymized, public, and freely available, informed consents were not needed nor ethical committee approval.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    The limitations of the present study and suggestions for future research are addressed. To compare deaths and cases by sex and age in a given date, we decided to consider data reported until September 30, 2020. In such records, we observed a series of sociodemographic aspects (like sex, age, and region of residence) of individuals reported as suspect cases of COVID-19 and the moment of detection of the disease in those who turned out to be positive cases. Additionally, they also record the date of death. However, it must be mentioned that such information is sensitive to manual data processing errors, and that ex post health authorities may submit the records to modifications and changes. That means, even if those data are updated continuously, they are not a replacement for the vital statistics provided by each country. Furthermore, not every death assigned to a positive case implies that COVID-19 was the cause of death. The present study’s objective is not to establish the “real” impact of mortality attributed to COVID-19 in Argentina and Colombia, but make an approximation given on the know information and the available sources. In conclusion, any death rate comparison that is not sex or age adjusted might lead to a misrepresentation of the actual differences of the pandemic impact between countries.

    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.

  2. Version published to 10.1101/2020.11.30.20239947v1 on medRxiv