Research article Special Issues

On the relationship between COVID-19 reported fatalities early in the pandemic and national socio-economic status predating the pandemic

  • Received: 30 March 2021 Accepted: 18 May 2021 Published: 24 May 2021
  • This study investigates the relationship between socio-economic determinants pre-dating the pandemic and the reported number of cases, deaths, and the ratio of deaths/cases in 199 countries/regions during the first months of the COVID-19 pandemic. The analysis is performed by means of machine learning methods. It involves a portfolio/ensemble of 32 interpretable models and considers the case in which the outcome variables (number of cases, deaths, and their ratio) are independent and the case in which their dependence is weighted based on geographical proximity. We build two measures of variable importance, the Absolute Importance Index (AII) and the Signed Importance Index (SII) whose roles are to identify the most contributing socio-economic factors to the variability of the COVID-19 pandemic. Our results suggest that, together with the established influence on cases and deaths of the level of mobility, the specific features of the health care system (smart/poor allocation of resources), the economy of a country (equity/non-equity), and the society (religious/not religious or community-based vs not) might contribute to the number of COVID-19 cases and deaths heterogeneously across countries.

    Citation: Kathleen Lois Foster, Alessandro Maria Selvitella. On the relationship between COVID-19 reported fatalities early in the pandemic and national socio-economic status predating the pandemic[J]. AIMS Public Health, 2021, 8(3): 439-455. doi: 10.3934/publichealth.2021034

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  • This study investigates the relationship between socio-economic determinants pre-dating the pandemic and the reported number of cases, deaths, and the ratio of deaths/cases in 199 countries/regions during the first months of the COVID-19 pandemic. The analysis is performed by means of machine learning methods. It involves a portfolio/ensemble of 32 interpretable models and considers the case in which the outcome variables (number of cases, deaths, and their ratio) are independent and the case in which their dependence is weighted based on geographical proximity. We build two measures of variable importance, the Absolute Importance Index (AII) and the Signed Importance Index (SII) whose roles are to identify the most contributing socio-economic factors to the variability of the COVID-19 pandemic. Our results suggest that, together with the established influence on cases and deaths of the level of mobility, the specific features of the health care system (smart/poor allocation of resources), the economy of a country (equity/non-equity), and the society (religious/not religious or community-based vs not) might contribute to the number of COVID-19 cases and deaths heterogeneously across countries.



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    Acknowledgments



    K.L.F. and A.M.S. thank their families for their constant support. This project was funded by Ball State University start-up funds awarded to K.L.F. and Purdue University Fort Wayne start-up funds awarded to A.M.S.

    Conflict of interest



    All authors declare no conflicts of interest in this paper.

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