<ns7:p><ns7:bold>Background: </ns7:bold>Social, geographic, economic, demographic, and health factors were analysed to identify some social determinants related to case fatality of COVID-19 in 67 countries.</ns7:p><ns7:p> <ns7:bold>Methods:</ns7:bold> A mixed generalized linear model with beta distribution with random intercept was used to estimate the effects of the explanatory variables on the lethality for COVID-19 in 67 countries.</ns7:p><ns7:p> <ns7:bold>Results:</ns7:bold> The case fatality rate (CFR) was highest in the countries with the highest percentages of people over 60 years of age, the highest number of hospital beds,the highest mortalit yrate from diabetes, and the highest number of COVID-19 tests. Additional increases were seen based on literacy rates, health investment, death rate from cardiovascular disease, poverty rate, ratio of men, number of air passengers mobilized, number of days from the first reported case to the start of quarantine, death rate from respiratory infections, and percentage of people living in urban areas.</ns7:p><ns7:p> <ns7:bold>Conclusions: </ns7:bold>The statistical model used to predict lethality is novel because it allows the magnitude of the CFR to be analysed over a logistic model that classifies countries considering the presence and absence of deaths. When considering a beta distribution with excess zeros, the model also allows countries without reported deaths due to COVID-19 at the analysed cut-off date to be included.</ns7:p>