Are men dying more than women by COVID-19?

  1. Thaise Pinto de Melo
  2. Delvan Alves Silva
  3. Alexandre Naime Barbosa

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Abstract

We aimed to clarify if the infection and death rate by COVID-19 differ among gender in the top 50 countries with the highest death rates. Also, we investigated if secondary variables such as HDI, number of hospital beds, average age, temperature, percentage of elderly, smoker and obesity are contributing to the variability observed among countries. Meta-analyses and meta-regressions approaches were applied to official public data reported by the Word Health Organization and governments until May, 2020. A random effect model was used for the meta-analysis and heterogeneity was calculated by I 2 statistic. There was not significative difference between men and women to be infected by COVID-19 ( P = 0.42), though a significative difference was observed for death rate ( P < 0.0001). High heterogeneity was observed among countries. For both infection and death rates this variability was mainly explained by the HDI (42.3% and 54.2%), average age (40.9% and 40.3%) and temperature (30.1% and 39.3%). Man are dying more than women around the word by COVID-19. Countries with highest HDI present less difference between sexes. These results reinforce that public politics promoting social isolation, health care and general well-being of the population are key factors in combating COVID-19.

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    SciScore for 10.1101/2020.07.06.20147629: (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 heterogeneity was accessed by using the Higgins’ and Thompson’s I2 statistic as:

    Where Q is the Cochrane Q statistic, obtained as , following a qui-squared distribution with k-1 degrees of freedom.

    Cochrane Q
    suggested: None

    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.

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  2. Version published to 10.1101/2020.07.06.20147629v1 on medRxiv