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

Big Data Mining and Analytics

Kumari Rajani¹  Agarwal Pankaj²  Poonia Ramesh Chandra²  Kumar Sandeep³  Singh Vijander⁴  Bhatnagar Vaibhav⁴  Raja Linesh⁴ 

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

关键词: covid-19;    regression;    correlation;    machine learning;    prediction;   

DOI  :  10.26599/BDMA.2020.9020013

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown