Women in power: Female leadership and public health outcomes during the COVID-19 pandemic

  1. Luca Coscieme
  2. Lorenzo Fioramonti
  3. Lars F. Mortensen
  4. Kate E. Pickett
  5. Ida Kubiszewski
  6. Hunter Lovins
  7. Jacqueline Mcglade
  8. Kristín Vala Ragnarsdóttir
  9. Debra Roberts
  10. Robert Costanza
  11. Roberto De Vogli
  12. Richard Wilkinson

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Abstract

Some countries have been more successful than others at dealing with the COVID-19 pandemic. When we explore the different policy approaches adopted as well as the underlying socio-economic factors, we note an interesting set of correlations: countries led by women leaders have fared significantly better than those led by men on a wide range of dimensions concerning the global health crisis. In this paper, we analyze available data for 35 countries, focusing on the following variables: number of deaths per capita due to COVID-19, number of days with reported deaths, peaks in daily deaths, deaths occurred on the first day of lockdown, and excess mortality. Results show that countries governed by female leaders experienced much fewer COVID-19 deaths per capita and were more effective and rapid at flattening the epidemic’s curve, with lower peaks in daily deaths. We argue that there are both contingent and structural reasons that may explain these stark differences. First of all, most women-led governments were more prompt at introducing restrictive measures in the initial phase of the epidemic, prioritizing public health over economic concerns, and more successful at eliciting collaboration from the population. Secondly, most countries led by women are also those with a stronger focus on social equality, human needs and generosity. These societies are more receptive to political agendas that place social and environmental wellbeing at the core of national policymaking.

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  1. Version published to 10.1101/2020.07.13.20152397v2 on medRxiv
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    SciScore for 10.1101/2020.07.13.20152397: (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
    In order to control for levels of mortality, we analyzed excess mortality from the Financial Times database on “excess mortality during the COVID-19 pandemic” compiled from multiple official sources (the full dataset is available at https://github.com/Financial-Times/coronavirus-excess-mortality-data).
    Financial Times
    suggested: None
    In order to explore possible relations between female leadership, impacts of COVID-19, and economic inequality, we have used the Gini coefficient, as well as the income share held by poorest 10% of the population (both from https://data.worldbank.org/).
    https://data.worldbank.org/
    suggested: (Data World Bank, RRID:SCR_012767)

    Results from OddPub: Thank you for sharing your code and data.

    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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  3. Version published to 10.1101/2020.07.13.20152397v1 on medRxiv