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The influence of underlying conditions of countries on the COVID-19 lethality rate

Abstract:

The management of the COVID-19 pandemic not only depends on the strin-gency measures established by governments but more importantly on the underlying capacity of territories in economic, health and sanitary infrastructure. This study aims to identify how the underlying conditions of countries influence their COVID-19 lethality rate. To do so, a classification of countries is first developed by the k-means partition-ing method, using COVID-19-related variables such as the lethality rate, the contagion growth rate and the number of days with respect to China. Based on the resulting groups of countries of the first stage, Tobit and Ordinary Least Squares regressions are estimated to determine the effect of the underlying characteristics of countries on their COVID-19 lethality rate. Risks factors which increase the lethality rate in countries are the contagion growth rate, the trade flow with China, the age composition of the population and, to a lesser extent, the population density. Factors that help reduce the lethality rate are the government effectiveness, the health infrastructure (hospital beds) and, to a lesser extent, the economic growth rate.