The COVID-19 pandemic: socioeconomic and health disparities

TL;DR

This study analyzes how socioeconomic and health disparities influence COVID-19 mortality, revealing that social disadvantage and demographics significantly correlate with higher death rates, emphasizing the pandemic's unequal impact.

Contribution

It identifies key socioeconomic and health-related factors associated with COVID-19 mortality using advanced predictive models on country-level data.

Findings

XGBoost outperformed ridge regression in prediction accuracy

Social disadvantage correlates strongly with higher COVID-19 mortality

Pre-existing inequalities amplify pandemic health impacts

Abstract

Disadvantaged groups around the world have suffered and endured higher mortality during the current COVID-19 pandemic. This contrast disparity suggests that socioeconomic and health-related factors may drive inequality in disease outcome. To identify these factors correlated with COVID-19 outcome, country aggregate data provided by the Lancet COVID-19 Commission subjected to correlation analysis. Socioeconomic and health-related variables were used to predict mortality in the top 5 most affected countries using ridge regression and extreme gradient boosting (XGBoost) models. Our data reveal that predictors related to demographics and social disadvantage correlate with COVID-19 mortality per million and that XGBoost performed better than ridge regression. Taken together, our findings suggest that the health consequence of the current pandemic is not just confined to indiscriminate impact of a viral infection but that these preventable effects are amplified based on pre-existing health and socioeconomic inequalities.