Analysis of the Influence of Social and Economic Factors on COVID-19 Cases with the Principal Component Analysis (PCA) Method

Abstract

Coronavirus Disease 2019 (COVID-19) is a disease caused by the SARS-CoV-2 virus which infects the human respiratory. On March 11, 2019, World Health Organization (WHO) officially declared the COVID-19 outbreak as a global pandemic because in less than three months it had infected more than 120,000 people in 123 countries from Asia, Europe, United States, to South Africa. This rapid growth of cases is caused by many factors. Therefore, the author wants to examine social and economic factors in 29 countries regarding the COVID-19 case. In this study, the author uses 122 variables; consisting of 107 variables from social factors and 15 variables from economic factors. Because the number of variables used was quite large, the author reduced the data using the Principal Component Analysis (PCA). Then, 15 main components are formed from the results of the application of PCA carried out on 122 variables. It will then be used to form a regression equation for the COVID-19 case which consists of the average new cases of COVID-19 per day, the rate of infected population COVID-19, the percentage of deaths caused by COVID-19, and the percentile of the new cases of COVID-19 per day.