Prediction of COVID-19 trend in India using time series forecasting

Objectives: COVID-19 pandemic is one of the prevalent challenges mankind has ever faced and there is a lot of uncertainty prevailing over the future with respect to COVID-19. In this situation machine learning algorithms can be useful for real-time analysis and prediction of trends of the infections. The objective of the research study is to analyze the COVID-19 trend in India and forecast the trend of outbreak in near future. This model can provisionally guide the government and healthcare organizations in making preparations for the upcoming situation arising out of COVID-19 transmission. Methods: The COVID-19 data from 30-Dec 2019 to 27-July 2020 was used for prediction of COVID-19 trend in next 30 days i.e. from 28 July to 26 August. The time series forecasting approaches with ARIMA Model and PROPHET were used for forecasting. The performance of these models was evaluated using validation metrics and good performance was indicated. Findings: The prediction results indicate an increasing trend of COVID-19 positive, active and deceased cases in India for next 30 days i.e. up to 26 August 2020. Novelty: COVID-19 pandemic is a new problem. The novelty and originality of this research lies in the fact that time series forecasting is used for real time analysis and prediction of COVID-19 pandemic.