Dynamic Model To Predict The Flattening Of The Covid-19 Outbreak Curve In India

This paper aims to forecast and visualize the confirmed cases, deaths, and recoveries of COVID-19 in India and also predict the end of the growth of COVID-19 cases in India. The methods used for the prediction of future COVID19 cases are machine learning techniques, improved logistic growth equation with a dynamic rate of infection, and automation of the calculations using Python programming language. The paper discusses the current models being used to predict the flattening of the curve, and the pros and cons of using these techniques. The paper then presents the solution and results achieved using our method. The average accuracy percentage of predictions of total confirmed cases was 85.6%, deaths were 84.5%, and recoveries were 83.8%. According to the predictions, the curve started to flatten in October and the curve will completely flatten in the 2nd week of January which confirms the situation that prevailed in India.