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Modeling of Total Cases due to COVID-19 and its Impact in India
This research paper focuses on the modeling of total cases due to COVID-19 and the critical assessment of socioeconomic impact on India. The data set considered for the present analysis is from December 31, 2019 to May 16, 2020 for training and testing of developed regression model. Least-square app...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885751/ http://dx.doi.org/10.1007/s40031-021-00558-w |
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author | Kulkarni, Kishor Kulkarni, Antara Shaikh, Naziya Sultana Sayyed, Siraj |
author_facet | Kulkarni, Kishor Kulkarni, Antara Shaikh, Naziya Sultana Sayyed, Siraj |
author_sort | Kulkarni, Kishor |
collection | PubMed |
description | This research paper focuses on the modeling of total cases due to COVID-19 and the critical assessment of socioeconomic impact on India. The data set considered for the present analysis is from December 31, 2019 to May 16, 2020 for training and testing of developed regression model. Least-square approximation of linear regression technique is applied to estimate the total cases of COVID-19. Three variables, viz. daily new cases, total deaths and daily new deaths, were considered for development of correlations. In the present study, seven correlations are developed as a function of single variable, two variables and three variables with accuracy (R(2)) ranging from 85.71 to 99.95%. The paper also highlights the socioeconomic impact of COVID 19 on different sector, challenges and remedies for improving the GDP of the country. |
format | Online Article Text |
id | pubmed-7885751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-78857512021-02-16 Modeling of Total Cases due to COVID-19 and its Impact in India Kulkarni, Kishor Kulkarni, Antara Shaikh, Naziya Sultana Sayyed, Siraj J. Inst. Eng. India Ser. B Original Contribution This research paper focuses on the modeling of total cases due to COVID-19 and the critical assessment of socioeconomic impact on India. The data set considered for the present analysis is from December 31, 2019 to May 16, 2020 for training and testing of developed regression model. Least-square approximation of linear regression technique is applied to estimate the total cases of COVID-19. Three variables, viz. daily new cases, total deaths and daily new deaths, were considered for development of correlations. In the present study, seven correlations are developed as a function of single variable, two variables and three variables with accuracy (R(2)) ranging from 85.71 to 99.95%. The paper also highlights the socioeconomic impact of COVID 19 on different sector, challenges and remedies for improving the GDP of the country. Springer India 2021-02-16 2021 /pmc/articles/PMC7885751/ http://dx.doi.org/10.1007/s40031-021-00558-w Text en © The Institution of Engineers (India) 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Contribution Kulkarni, Kishor Kulkarni, Antara Shaikh, Naziya Sultana Sayyed, Siraj Modeling of Total Cases due to COVID-19 and its Impact in India |
title | Modeling of Total Cases due to COVID-19 and its Impact in India |
title_full | Modeling of Total Cases due to COVID-19 and its Impact in India |
title_fullStr | Modeling of Total Cases due to COVID-19 and its Impact in India |
title_full_unstemmed | Modeling of Total Cases due to COVID-19 and its Impact in India |
title_short | Modeling of Total Cases due to COVID-19 and its Impact in India |
title_sort | modeling of total cases due to covid-19 and its impact in india |
topic | Original Contribution |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7885751/ http://dx.doi.org/10.1007/s40031-021-00558-w |
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