Title: Forecasting the coronavirus disease 2019 pandemic in India using machine learning and statistical models

Authors: Sidharth Saxena; Rajashree Shettar

Addresses: Department of Biotechnology, Ramaiah Institute of Technology, Bengaluru, Karnataka, India ' Department of Computer Science and Engineering, RV College of Engineering®, Bengaluru, Karnataka, India

Abstract: COVID-19, which is an infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has resulted in a massive blow to India with respect to the health of its citizens and economy. The work in this paper focuses on the Prophet model, linear regression model, Holt's model and the ARIMA model for predicting the number of confirmed, recovered cases, deaths and active cases along with growth rate, recovery rate and mortality rate in India for the month of November 2020. The performance of all the above mentioned models has been evaluated using standard metrics namely R², adjusted R², root-mean-square error and mean absolute error.

Keywords: linear regression model; Prophet model; Holt's model; ARIMA model; COVID-19; forecasting; India.

DOI: 10.1504/IJMMNO.2022.123973

International Journal of Mathematical Modelling and Numerical Optimisation, 2022 Vol.12 No.3, pp.211 - 232

Received: 07 Apr 2021
Accepted: 20 Aug 2021
Published online: 05 Jul 2022 *

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