Mathematical Modeling of COVID-19 and Prediction of Upcoming Wave

Abstract

We investigate the problem of mathematical modeling of new corona virus (COVID-19) spread in practical scenarios in various countries, specifically in India, the United States of America (USA), France, Brazil, and Turkey. We propose a mathematical model to characterize COVID-19 disease and predict the new/upcoming wave of COVID-19. This prediction is very much required to prepare medical set-ups and proceed with future plans of action. A mixture Gaussian model is proposed to characterize the COVID-19 disease. Specifically, the data corresponding to new active cases of COVID-19 per day is considered, and then we try to fit the data to a mathematical function. It is observed that the Gaussian mixture model is suitable to characterize the new active cases of COVID-19. Further, it is assumed that there are N waves of COVID-19 and the information of each upcoming wave is present in the current and previous waves as well. By using this concept, prediction of the upcoming wave can be performed. A close match between analytical results and the available results shows the correctness of the considered model.