Statistical Modeling of deaths due to COVID-19 influenced by social isolation in Latin American countries

Abstract

Social isolation is extremely important to minimize the effects of a pandemic. Latin American (LA) countries have similar socioeconomic characteristics and health system infrastructures. These countries face difficulties to deal with the COVID-19 pandemic and some of them had very high death rates. Government stringency index (GSI) of twelve LA countries was gathered from the Oxford COVID-19 Government Response Tracker (OxCGRT) project. GSI was calculated considering nine metrics such as school and work closures, stay-at-home requirements, among others types of social distancing and isolation measures. Population data from the United Nations Population Fund and number of deaths data was collected from the dashboard of the World Health Organization (WHO). We performed an analysis of the period March-December using a mixed linear model approach. Peru, Brazil, Chile, Bolivia, Colombia, Argentina and Ecuador had the highest death rates with an increasing trend over time, while Suriname, Venezuela, Uruguay, Paraguay and Guyana had the lowest ones, which remained steady. GSI in most countries followed the same pattern during the analyzed months. i.e., high indices at the beginning of the pandemic and lower ones in the last evaluated months, while the number of deaths increased over the whole period. Almost no country kept its GSI high for much time, especially from October to December. Time and GSI as well as their interaction were highly significant. As their interaction increases, death rate decreases. In conclusion, our statistical model explains and substantiates the need for maintaining social distancing and isolation measures over time during the pandemic.