Model Base Analysis of COVID-19 Daily Infected Cases in Argentina

The COVID-19 first appeared in 2019. According to the World Health Organization (WHO) reports there were 184,222,453 infected cases and 3,987,180 death total reported globally after one year. Argentina had been the second Latin American country severely hit by the COVID-19. The rate of daily infected cases in Argentina was 10%, approximately. Hence, the study is designed to forecast the daily infected cases of COVID -19 in Argentina. The daily infected cases of Argentina for the period of 22nd January 2020 to 6th July 2021 were obtained from the WHO database. The behavior of the daily infected cases examined by time series plots and Auto Correlation Function (ACF). The Sama Circular Model (SCM), Seasonal Auto-Regressive Integrated Moving Average (SARIMA), and Holt’s Winters three-parameter additive and multiplicative models were tested to forecast the daily infected cases. The models were validated by applying the ACF, Anderson Darling test, and Ljung-Box Q (LBQ)-test. Both relative and absolute measurements of errors were used to assess the forecasting ability of the fitted models. The results of the study revealed that the SCM is a suitable model in forecasting daily infected cases of COVID -19 in Argentina, but not SARIMA and Holt's Winters models. It is recommended to conduct similar studies for other countries to capture similar behaviors and find the causes behind the seasonal behaviors of the rise and fall of daily infected cases