Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020)
Introduction: and Aims: No valid treatment or preventative strategy has evolved till date to counter the SARS CoV 2 (Novel Coronavirus) epidemic that originated in China in late 2019 and have since wrought havoc on millions across the world with illness, socioeconomic recession and death. This analy...
- Autores:
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Universidad de Bogotá Jorge Tadeo Lozano
- Repositorio:
- Expeditio: repositorio UTadeo
- Idioma:
- eng
- OAI Identifier:
- oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/12036
- Palabra clave:
- India
Coronavirus
Death rates
Correlation
Regression
Síndrome respiratorio agudo grave
COVID-19
SARS-CoV-2
Coronavirus
- Rights
- License
- Acceso restringido
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oai_identifier_str |
oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/12036 |
network_acronym_str |
UTADEO2 |
network_name_str |
Expeditio: repositorio UTadeo |
repository_id_str |
|
dc.title.spa.fl_str_mv |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
title |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
spellingShingle |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) India Coronavirus Death rates Correlation Regression Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
title_short |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
title_full |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
title_fullStr |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
title_full_unstemmed |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
title_sort |
Linear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020) |
dc.subject.spa.fl_str_mv |
India Coronavirus Death rates Correlation Regression |
topic |
India Coronavirus Death rates Correlation Regression Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
dc.subject.lemb.spa.fl_str_mv |
Síndrome respiratorio agudo grave COVID-19 SARS-CoV-2 Coronavirus |
description |
Introduction: and Aims: No valid treatment or preventative strategy has evolved till date to counter the SARS CoV 2 (Novel Coronavirus) epidemic that originated in China in late 2019 and have since wrought havoc on millions across the world with illness, socioeconomic recession and death. This analysis was aimed at tracing a trend related to death counts expected at the 5th and 6th week of the COVID-19 in India. Material and methods: Validated database was used to procure global and Indian data related to coronavirus and related outcomes. Multiple regression and linear regression analyses were used interchangeably. Since the week 6 death count data was not correlated significantly with any of the chosen inputs, an auto-regression technique was employed to improve the predictive ability of the regression model. Results: A linear regression analysis predicted average week 5 death count to be 211 with a 95% CI: 1.31 e2.60). Similarly, week 6 death count, in spite of a strong correlation with input variables, did not pass the test of statistical significance. Using auto-regression technique and using week 5 death count as input the linear regression model predicted week 6 death count in India to be 467, while keeping at the back of our mind the risk of over-estimation by most of the risk-based models. Conclusion: According to our analysis, if situation continue in present state; projected death rate (n) is 211 and467 at the end of the 5th and 6th week from now, respectively. |
publishDate |
2020 |
dc.date.accessioned.none.fl_str_mv |
2020-08-20T19:25:27Z |
dc.date.available.none.fl_str_mv |
2020-08-20T19:25:27Z |
dc.date.created.none.fl_str_mv |
2020 |
dc.type.local.spa.fl_str_mv |
Artículo |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
format |
http://purl.org/coar/resource_type/c_6501 |
dc.identifier.issn.spa.fl_str_mv |
1871-4021 |
dc.identifier.other.spa.fl_str_mv |
https://doi.org/10.1016/j.dsx.2020.03.017 |
dc.identifier.uri.none.fl_str_mv |
http://hdl.handle.net/20.500.12010/12036 |
dc.identifier.doi.spa.fl_str_mv |
https://doi.org/10.1016/j.dsx.2020.03.017 |
identifier_str_mv |
1871-4021 |
url |
https://doi.org/10.1016/j.dsx.2020.03.017 http://hdl.handle.net/20.500.12010/12036 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_f1cf |
dc.rights.local.spa.fl_str_mv |
Acceso restringido |
rights_invalid_str_mv |
Acceso restringido http://purl.org/coar/access_right/c_f1cf |
dc.format.extent.spa.fl_str_mv |
5 páginas |
dc.format.mimetype.spa.fl_str_mv |
image/jepg |
dc.publisher.spa.fl_str_mv |
Diabetes & Metabolic Syndrome: Clinical Research & Reviews |
dc.source.spa.fl_str_mv |
reponame:Expeditio Repositorio Institucional UJTL instname:Universidad de Bogotá Jorge Tadeo Lozano |
instname_str |
Universidad de Bogotá Jorge Tadeo Lozano |
institution |
Universidad de Bogotá Jorge Tadeo Lozano |
reponame_str |
Expeditio Repositorio Institucional UJTL |
collection |
Expeditio Repositorio Institucional UJTL |
bitstream.url.fl_str_mv |
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bitstream.checksum.fl_str_mv |
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bitstream.checksumAlgorithm.fl_str_mv |
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repository.name.fl_str_mv |
Repositorio Institucional - Universidad Jorge Tadeo Lozano |
repository.mail.fl_str_mv |
expeditio@utadeo.edu.co |
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1814213921383383040 |
spelling |
2020-08-20T19:25:27Z2020-08-20T19:25:27Z20201871-4021https://doi.org/10.1016/j.dsx.2020.03.017http://hdl.handle.net/20.500.12010/12036https://doi.org/10.1016/j.dsx.2020.03.017Introduction: and Aims: No valid treatment or preventative strategy has evolved till date to counter the SARS CoV 2 (Novel Coronavirus) epidemic that originated in China in late 2019 and have since wrought havoc on millions across the world with illness, socioeconomic recession and death. This analysis was aimed at tracing a trend related to death counts expected at the 5th and 6th week of the COVID-19 in India. Material and methods: Validated database was used to procure global and Indian data related to coronavirus and related outcomes. Multiple regression and linear regression analyses were used interchangeably. Since the week 6 death count data was not correlated significantly with any of the chosen inputs, an auto-regression technique was employed to improve the predictive ability of the regression model. Results: A linear regression analysis predicted average week 5 death count to be 211 with a 95% CI: 1.31 e2.60). Similarly, week 6 death count, in spite of a strong correlation with input variables, did not pass the test of statistical significance. Using auto-regression technique and using week 5 death count as input the linear regression model predicted week 6 death count in India to be 467, while keeping at the back of our mind the risk of over-estimation by most of the risk-based models. Conclusion: According to our analysis, if situation continue in present state; projected death rate (n) is 211 and467 at the end of the 5th and 6th week from now, respectively.5 páginasimage/jepgengDiabetes & Metabolic Syndrome: Clinical Research & Reviewsreponame:Expeditio Repositorio Institucional UJTLinstname:Universidad de Bogotá Jorge Tadeo LozanoIndiaCoronavirusDeath ratesCorrelationRegressionSíndrome respiratorio agudo graveCOVID-19SARS-CoV-2CoronavirusLinear Regression Analysis to predict the number of deaths in India due to SARS-CoV-2 at 6 weeks from day 0 (100 cases - March 14th 2020)Artículohttp://purl.org/coar/resource_type/c_6501Acceso restringidohttp://purl.org/coar/access_right/c_f1cfGhosal, SamitSengupta, SumitMajumder, MilanSinha, BinayakTHUMBNAILCaptura.PNGCaptura.PNGPortadaimage/png185512https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12036/4/Captura.PNGef4673b49695118226ad5bdab07525bbMD54open accessLinear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdf.jpgLinear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdf.jpgIM Thumbnailimage/jpeg14858https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12036/5/Linear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdf.jpg428eceb465cfb23105fa6c5faf06f4abMD55open accessORIGINALCaptura.PNGCaptura.PNGVer portadaimage/png185512https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12036/1/Captura.PNGef4673b49695118226ad5bdab07525bbMD51open accessLinear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdfLinear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdfArtículo reservadoapplication/pdf229894https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12036/3/Linear-Regression-Analysis-to-predict-the-number-o_2020_Diabetes---Metabolic.pdf854d4a9c093d48e1d5aa297403ef777fMD53open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-82938https://expeditiorepositorio.utadeo.edu.co/bitstream/20.500.12010/12036/2/license.txtabceeb1c943c50d3343516f9dbfc110fMD52open access20.500.12010/12036oai:expeditiorepositorio.utadeo.edu.co:20.500.12010/120362020-08-20 14:25:27.735open accessRepositorio Institucional - Universidad Jorge Tadeo Lozanoexpeditio@utadeo.edu.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 |