Forecasting of COVID-19 Cases Using SARIMA Model in India

On January 30, 2020, the World Health Organization (WHO) declared a global healthemergency for coronavirus disease 2019 (COVID-19). The disease spread around the world and on March11, 2020, it was declared a global pandemic by the WHO. India reported the very first case of COVID-19 onJanuary 30, 2020, and a complete lockdown on the country was announced on March 25, 2020, after WHOannounced that it was a global pandemic. Since then, India has reported 586K confirmed cases, of which348K have been cured, 17.4K died and 220K is still active as of June 30, 2020. In this work, a predictivemodel for the seasonal autoregressive integrated moving average (SARIMA or seasonal ARIMA) isproposed to predict the total number of confirmed, recovered, and deceased cases due to the COVID-19virus in India within the next 30 days from a selected date. The SARIMA model uses the Box-Jenkinsmodel, a forecasting method using regression studies. Data for this study has been taken from governmentwebsites from January 30, 2020, to June 30, 2020. Using the Tkinter library in Python 3.8, a graphical userinterface (GUI) is also developed to make this prediction model user-friendly. The accuracy in predictingCOVID-19 cases in this study is 99.7% in confirmed cases, 99.15% in recovered cases, and 99.08% indeceased cases.