A global spatial analysis of factors associated with case and mortality rates for coronavirus disease 2019 during the first year of the pandemic

Abstract

ABSTRACT Background A increasing number of studies have revealed associations between country-level determinants and coronavirus disease 2019 (COVID-19) outcomes. This ecological study was conducted to analyze country-level parameters related to COVID-19 infections and deaths during the first year of the pandemic. Methods The examined predictors comprised demographics, economic factors, disease prevalence and healthcare system status, and the relevant data were obtained from public databases. The index dates were set to 15 July 2020 (Time 1) and 15 December 2020 (Time 2). The adjusted spatial autoregression models used a first-order queen contiguity spatial weight for the main analysis and a second-order queen contiguity spatial weight for a sensitivity analysis to examine the predictors associated with COVID-19 case and mortality rates. Results Obesity was significantly and positively associated with COVID-19 case and mortality rates in both the main and sensitivity analyses. The sensitivity analysis revealed that a country's gross domestic product, population density, life expectancy and proportion of the population older than 65 y are positively associated with COVID-19 case and mortality rates. Conclusions With the increasing global prevalence of obesity, the relationship between obesity and COVID-19 disease at the country level must be clarified and continually monitored.