Numerical estimation of new COVID-19 positive cases using time series analysis by machine learning

As described herein, we propose a method to make more accurate predictions based on COVID-19 positive case data from Tokyo, which are provided as open data. Our proposed method uses prediction results of related variables to infer an objective function. Prediction of the number of infected people in Tokyo based on this method yielded better correlation between the predicted results and the actual number of COVID-19 positive cases than prediction of the number of infected people. Results also showed better correlation between prediction results and the actual number of COVID-19 positive cases than prediction based on the number of infected cases alone, indicating that our prediction method provides higher accuracy. © 2021 ACM.