Determinants of mortality rates from COVID-19: a macro level analysis by extended-beta regression model

Abstract

Objective The specific mortality rate (MR) due to COVID-19 is a useful indicator for monitoring and evaluating the health strategies of health systems in the pandemic era. The main objective of this study is to estimate the effects of social, health, and economic factors on MRs in 176 countries. Material and Methods Beta regression models were used, and MRs were estimated as the total number of deaths divided by the total number of confirmed cases (infection fatality rate) until December 2, 2021. Results The primary findings revealed heterogeneity in mortality rates between regions and countries. The estimated coefficients showed different patterns of association between the explanatory variables and mortality rates. In the American region, the results showed a strange pattern and nearly insignificant effect for almost all variables. In Asian countries, we found a significant effect of GDP per capita and the share of the population aged 65 years and older on mortality rates, whereas on the African continent, the significant variables affecting mortality rates were GDP per capita, human development index, and share of population aged 65 years and older. Finally, in the European region, we did not find clear evidence of an association between the explanatory variables and mortality rates. Conclusion These results show, in a heterogeneous way among regions, the impact of aging, development level and population density (especially with forms of distancing) on increasing the risk of death from the coronavirus. In conclusion, the pandemic has succeeded in demonstrating chaotic patterns of associations with social, health, and economic factors.