An Exploratory Analysis of COVID-19 in South America

Abstract

In the context of the COVID-19 pandemic, in the present work, we will use two main data visualization techniques, which are Cluster Analysis and Principal Component Analysis Biplot, over a dataset focused on South America; it contains variables related to both, economy and public health in South American countries; namely total cases, total tests, total deaths in public health case and GDP growth or Unemployment Rate in economic, we also considered a very important variable in this study which is the stringency index, it is the severity of the restrictions applied by each country to control the number of infected people. The mentioned analysis allowed us to lead to conclusions on which countries in South America had the best outcomes handling the pandemic in terms of public health and economic variables. By the time in which data was acquired - July 9th -, we found that Chile, Uruguay, and Paraguay could be named as the countries which better handled the pandemic in South America and will have a good economic recuperation in the upcoming years, on the other hand; Brazil, Argentina, Colombia, and Venezuela were the most affected countries due to the pandemic and will also be the ones with the slowest economic recuperation.