Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India
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. Thi...
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2021-06-01
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| Series: | Big Data Mining and Analytics |
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| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2020.9020013 |
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| author | Rajani Kumari Sandeep Kumar Ramesh Chandra Poonia Vijander Singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal |
| author_facet | Rajani Kumari Sandeep Kumar Ramesh Chandra Poonia Vijander Singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal |
| author_sort | Rajani Kumari |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c20041290c6e4b72ab71e748e32daaf9 |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2021-06-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-c20041290c6e4b72ab71e748e32daaf92025-02-02T23:47:56ZengTsinghua University PressBig Data Mining and Analytics2096-06542021-06-0142657510.26599/BDMA.2020.9020013Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in IndiaRajani Kumari0Sandeep Kumar1Ramesh Chandra Poonia2Vijander Singh3Linesh Raja4Vaibhav Bhatnagar5Pankaj Agarwal6<institution content-type="dept">Department of Information Technology and Computer Application</institution>, <institution>JECRC University, Jaipur</institution>, <city>Rajasthan</city> <postal-code>303905</postal-code>, <country>India</country><institution>CHRIST (Deemed to be University),Bangalore</institution>, <city>Karnataka</city> <postal-code>560029</postal-code>, <country>India</country><institution>Amity University Rajasthan, Jaipur</institution>, <city>Rajasthan</city> <postal-code>303002</postal-code>, <country>India</country><institution>Manipal University Jaipur</institution>, <city>Rajasthan</city> <postal-code>303007</postal-code>, <country>India</country><institution>Manipal University Jaipur</institution>, <city>Rajasthan</city> <postal-code>303007</postal-code>, <country>India</country><institution>Manipal University Jaipur</institution>, <city>Rajasthan</city> <postal-code>303007</postal-code>, <country>India</country><institution>Amity University Rajasthan, Jaipur</institution>, <city>Rajasthan</city> <postal-code>303002</postal-code>, <country>India</country>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.https://www.sciopen.com/article/10.26599/BDMA.2020.9020013covid-19regressioncorrelationmachine learningprediction |
| spellingShingle | Rajani Kumari Sandeep Kumar Ramesh Chandra Poonia Vijander Singh Linesh Raja Vaibhav Bhatnagar Pankaj Agarwal Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India Big Data Mining and Analytics covid-19 regression correlation machine learning prediction |
| title | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India |
| title_full | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India |
| title_fullStr | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India |
| title_full_unstemmed | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India |
| title_short | Analysis and Predictions of Spread, Recovery, and Death Caused by COVID-19 in India |
| title_sort | analysis and predictions of spread recovery and death caused by covid 19 in india |
| topic | covid-19 regression correlation machine learning prediction |
| url | https://www.sciopen.com/article/10.26599/BDMA.2020.9020013 |
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