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

Abstract

Background and AimsThe 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.MethodsWe 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.ResultsThere 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.ConclusionThe 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.