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Open Access

Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India

Department of Information Technology and Computer Application, JECRC University, Jaipur, Rajasthan 303905, India
CHRIST (Deemed to be University),Bangalore, Karnataka 560029, India
Amity University Rajasthan, Jaipur, Rajasthan 303002, India
Manipal University Jaipur, Rajasthan 303007, India
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Abstract

The novel coronavirus outbreak was first reported in late December 2019 and more than 7 million people were infected with this disease and over 0.40 million worldwide lost their lives. The first case was diagnosed on 30 January 2020 in India and the figure crossed 0.24 million as of 6 June 2020. This paper presents a detailed study of recently developed forecasting models and predicts the number of confirmed, recovered, and death cases in India caused by COVID-19. The correlation coefficients and multiple linear regression applied for prediction and autocorrelation and autoregression have been used to improve the accuracy. The predicted number of cases shows a good agreement with 0.9992 R-squared score to the actual values. The finding suggests that lockdown and social distancing are two important factors that can help to suppress the increasing spread rate of COVID-19.

Keywords

COVID-19regressioncorrelationmachine learningprediction

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Big Data Mining and Analytics
Volume 4 Issue 2,
June 2021
Pages 65-75
DOI: 10.26599/BDMA.2020.9020013
Cite this article:
Kumari R, Kumar S, Poonia RC, et al. Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India. Big Data Mining and Analytics, 2021, 4(2): 65-75. https://doi.org/10.26599/BDMA.2020.9020013

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Received: 07 May 2020
Revised: 14 June 2020
Accepted: 28 July 2020
Published: 01 February 2021
© The author(s) 2021

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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