Socioeconomic status and COVID-19-related cases and fatalities in the world: A cross-sectional ecological study.

BACKGROUND AND AIMS

The COVID-19 pandemic poses an extraordinary threat to global public health. We designed an ecological study to explore the association between socioeconomic factors and the COVID-19 outcomes in 184 countries, using the geographic map and multilevel regression models.

METHODS

We conducted a cross-sectional ecological study in 184 countries. We performed regression analysis to assess the association of various socioeconomic variables with COVID-19 outcomes in 184 countries, using ordinary least squares and multilevel modeling analysis. We performed two-level analyses with countries at Level 1 and geographical regions at Level 2 in multilevel modeling analysis, using the same set of predictor variables used in ordinary least squares.

RESULTS

There was a significant relationship between COVID-19 cases rate (Log) per 100,000 inhabitants-day at risk with human development index (HDI), percentage of the urban population, unemployment, and cardiovascular disease prevalence. The results displayed that the variances are varied between Level 1 (country level) and Level 2 (World Health Organization [WHO] regions), meaning that the geographic distribution represented a proportion of the changes in the COVID-19 outcomes.

CONCLUSION

The study suggests that in addition to the socioeconomic status affects the COVID-19 outcomes, countries' geographical location makes a part of changes in outcomes of diseases. Therefore, health policy-makers could overcome morbidity and mortality in COVID-19 by controlling the socioeconomics factors.