Title: Prediction of COVID-19 epidemic curve of India using supervised learning approach

Authors: Shweta Mongia; Sugandha Sharma; Jaisankar Natarajan; Manoj Kumar; Vasudha Arora; Thompson Stephan; Achyut Shankar; Pragya Gupta; Raghav Kachhawaha

Addresses: Department of Computer Science and Engineering, Faculty of Engineering, Manav Rachna International Institute of Research and Studies, Haryana, India ' School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department-CSE, VIT Vellore, Vellore, Tamil Nadu, India ' School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' Department of Computer Science, GD Goenka University, Gurugram, Haryana, India ' Department of Computer Science and Engineering, Faculty of Engineering and Technology, M.S. Ramaiah University of Applied Sciences, Bangalore, Karnataka, India ' Department of Computer Science & Engineering, Amity School of Engineering and Technology, Amity University (UP) Noida, Uttar Pradesh, India ' School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India ' School of Computer Science, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India

Abstract: The recent outbreak of the COVID-19 pandemic, a neo zoonotic infectious disease, has caused high mortality worldwide. The need of the hour is to equip the governments with early detection, prevention, and mitigation of such contagious diseases. In this paper, a supervised learning approach of the polynomial regression model is used for the prediction of COVID-19 cases in terms of the number of confirmed cases (CC), death cases (DC), and recovered cases (RC) in India. Authors have also predicted death rates and recovery rates. The recovery rate on 25th April 2020 is 21.97% and by 1st June 2020 this rate will increase to 79%. In addition to this, authors have projected a monthly percentage increase in the number of CC from 1st May 2020 to 1st December 2020. This analysis would help and enable the concerned authorities in bringing effective preventive measures into action in the process of decision making.

Keywords: supervised learning; polynomial regression model; COVID-19; prediction; epidemic curve.

DOI: 10.1504/IJCAT.2021.120469

International Journal of Computer Applications in Technology, 2021 Vol.66 No.3/4, pp.433 - 441

Received: 16 Jul 2020
Accepted: 17 Dec 2020
Published online: 21 Jan 2022 *

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