Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020
Descripción del Articulo
Objective: To prove through an econometric model the number of deaths in Peru is significantly related to the number of infected cases of COVID-19. Method: Basic research, not experimental. For the whole country of Peru, 52 series (days) have been taken and in the specific case from the department o...
Autores: | , , |
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Formato: | artículo |
Fecha de Publicación: | 2020 |
Institución: | Universidad Nacional Mayor de San Marcos |
Repositorio: | Revista UNMSM - Quipukamayoc |
Lenguaje: | español |
OAI Identifier: | oai:ojs.csi.unmsm:article/18396 |
Enlace del recurso: | https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396 |
Nivel de acceso: | acceso abierto |
Materia: | Coronavirus COVID 19 tests deceased infected econometric model exámenes COVID 19 fallecidos infectados modelos econométricos |
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Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020Validación de un modelo econométrico de letalidad por infectados COVID-19, Perú Mayo 2020Flores Arocutipa, Javier PedroJinchuña Huallpa, JorgeCondori Perez, Roberto TitoCoronavirusCOVID 19 testsdeceasedinfectedeconometric modelCoronavirusexámenes COVID 19fallecidosinfectadosmodelos econométricosObjective: To prove through an econometric model the number of deaths in Peru is significantly related to the number of infected cases of COVID-19. Method: Basic research, not experimental. For the whole country of Peru, 52 series (days) have been taken and in the specific case from the department of Moquegua, 37 series in the period from March 16 until May 10, 2020. The database of the Ministry of Health has been used, the COVID-19 Situation Chamber and the Moquegua Regional Health Management; Pearson's R and R2 are used. Regression models were generated on May 10 (after 52 days after the first death), which must be contrasted on May 31. Results: The models comply with the prediction, with a high and significant R2 and Rho. Conclusions: The death prediction models are corroborated as of May 31, 73 days after the first death in Peru. Pearson's correlation and determination levels in countries which are coming up from the COVID-19 emergency, regions throughout Peru have a high and significant relationship between infected and deceased. The bigger number of infected, the bigger number of deaths. In number and proportion are adults and older adults. 72.5% are male. In Moquegua it is shown the relationship between the levels of diagnostic tests performed and infected.Objetivo: Probar mediante un modelo econométrico que la cantidad de los fallecidos en el Perú se relacionan de manera significativa con el número de casos infectados de COVID- 19. Método: Investigación de tipo básica, no experimental. Para todo el Perú se ha tomado 52 series (días) y en el caso específico del departamento de Moquegua, 37 series en el periodo del 16 de marzo al 10 de mayo del 2020. Se ha utilizado la base de datos del Ministerio de Salud, de la Sala situacional COVID-19 y de la Gerencia Regional de Salud de Moquegua; se emplea el R y R2 de Pearson. Se generaron modelos de regresión el 10 de mayo (luego de 52 días del primer fallecido), que deben ser contrastados el 31 de mayo. Resultados: Los modelos cumplen con la predicción, con un R2 y un Rho altos y significativos. Conclusiones: Los modelos de predicción de fallecidos son corroborados al 31 de mayo, luego de 73 días del primer fallecido en el Perú. Los niveles de correlación y determinación de Pearson en países que están saliendo de la emergencia del COVID-19, las regiones de todo el Perú tienen una alta y significativa relación entre infectados y fallecidos. A mayor número de infectados mayor número de fallecidos. En número y proporción son adultos y adultos mayores. En un 72,5% son varones. En Moquegua se demuestra que hay relación entre los niveles de exámenes diagnósticos realizados e infectados.Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables2020-08-31info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/1839610.15381/quipu.v28i57.18396Quipukamayoc; Vol 28 No 57 (2020); 17-23Quipukamayoc; Vol. 28 Núm. 57 (2020); 17-231609-81961560-9103reponame:Revista UNMSM - Quipukamayocinstname:Universidad Nacional Mayor de San Marcosinstacron:UNMSMspahttps://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396/15758https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396/15771Derechos de autor 2020 Javier Pedro Flores Arocutipa, Jorge Jinchuña Huallpa, Roberto Tito Condori Perezhttp://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccess2021-06-01T17:32:24Zmail@mail.com - |
dc.title.none.fl_str_mv |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 Validación de un modelo econométrico de letalidad por infectados COVID-19, Perú Mayo 2020 |
title |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
spellingShingle |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 Flores Arocutipa, Javier Pedro Coronavirus COVID 19 tests deceased infected econometric model Coronavirus exámenes COVID 19 fallecidos infectados modelos econométricos |
title_short |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
title_full |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
title_fullStr |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
title_full_unstemmed |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
title_sort |
Lethality econometric model validity for COVID-19 infected pleople, Peru May 2020 |
dc.creator.none.fl_str_mv |
Flores Arocutipa, Javier Pedro Jinchuña Huallpa, Jorge Condori Perez, Roberto Tito |
author |
Flores Arocutipa, Javier Pedro |
author_facet |
Flores Arocutipa, Javier Pedro Jinchuña Huallpa, Jorge Condori Perez, Roberto Tito |
author_role |
author |
author2 |
Jinchuña Huallpa, Jorge Condori Perez, Roberto Tito |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Coronavirus COVID 19 tests deceased infected econometric model Coronavirus exámenes COVID 19 fallecidos infectados modelos econométricos |
topic |
Coronavirus COVID 19 tests deceased infected econometric model Coronavirus exámenes COVID 19 fallecidos infectados modelos econométricos |
dc.description.none.fl_txt_mv |
Objective: To prove through an econometric model the number of deaths in Peru is significantly related to the number of infected cases of COVID-19. Method: Basic research, not experimental. For the whole country of Peru, 52 series (days) have been taken and in the specific case from the department of Moquegua, 37 series in the period from March 16 until May 10, 2020. The database of the Ministry of Health has been used, the COVID-19 Situation Chamber and the Moquegua Regional Health Management; Pearson's R and R2 are used. Regression models were generated on May 10 (after 52 days after the first death), which must be contrasted on May 31. Results: The models comply with the prediction, with a high and significant R2 and Rho. Conclusions: The death prediction models are corroborated as of May 31, 73 days after the first death in Peru. Pearson's correlation and determination levels in countries which are coming up from the COVID-19 emergency, regions throughout Peru have a high and significant relationship between infected and deceased. The bigger number of infected, the bigger number of deaths. In number and proportion are adults and older adults. 72.5% are male. In Moquegua it is shown the relationship between the levels of diagnostic tests performed and infected. Objetivo: Probar mediante un modelo econométrico que la cantidad de los fallecidos en el Perú se relacionan de manera significativa con el número de casos infectados de COVID- 19. Método: Investigación de tipo básica, no experimental. Para todo el Perú se ha tomado 52 series (días) y en el caso específico del departamento de Moquegua, 37 series en el periodo del 16 de marzo al 10 de mayo del 2020. Se ha utilizado la base de datos del Ministerio de Salud, de la Sala situacional COVID-19 y de la Gerencia Regional de Salud de Moquegua; se emplea el R y R2 de Pearson. Se generaron modelos de regresión el 10 de mayo (luego de 52 días del primer fallecido), que deben ser contrastados el 31 de mayo. Resultados: Los modelos cumplen con la predicción, con un R2 y un Rho altos y significativos. Conclusiones: Los modelos de predicción de fallecidos son corroborados al 31 de mayo, luego de 73 días del primer fallecido en el Perú. Los niveles de correlación y determinación de Pearson en países que están saliendo de la emergencia del COVID-19, las regiones de todo el Perú tienen una alta y significativa relación entre infectados y fallecidos. A mayor número de infectados mayor número de fallecidos. En número y proporción son adultos y adultos mayores. En un 72,5% son varones. En Moquegua se demuestra que hay relación entre los niveles de exámenes diagnósticos realizados e infectados. |
description |
Objective: To prove through an econometric model the number of deaths in Peru is significantly related to the number of infected cases of COVID-19. Method: Basic research, not experimental. For the whole country of Peru, 52 series (days) have been taken and in the specific case from the department of Moquegua, 37 series in the period from March 16 until May 10, 2020. The database of the Ministry of Health has been used, the COVID-19 Situation Chamber and the Moquegua Regional Health Management; Pearson's R and R2 are used. Regression models were generated on May 10 (after 52 days after the first death), which must be contrasted on May 31. Results: The models comply with the prediction, with a high and significant R2 and Rho. Conclusions: The death prediction models are corroborated as of May 31, 73 days after the first death in Peru. Pearson's correlation and determination levels in countries which are coming up from the COVID-19 emergency, regions throughout Peru have a high and significant relationship between infected and deceased. The bigger number of infected, the bigger number of deaths. In number and proportion are adults and older adults. 72.5% are male. In Moquegua it is shown the relationship between the levels of diagnostic tests performed and infected. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-08-31 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396 10.15381/quipu.v28i57.18396 |
url |
https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396 |
identifier_str_mv |
10.15381/quipu.v28i57.18396 |
dc.language.none.fl_str_mv |
spa |
language |
spa |
dc.relation.none.fl_str_mv |
https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396/15758 https://revistasinvestigacion.unmsm.edu.pe/index.php/quipu/article/view/18396/15771 |
dc.rights.none.fl_str_mv |
Derechos de autor 2020 Javier Pedro Flores Arocutipa, Jorge Jinchuña Huallpa, Roberto Tito Condori Perez http://creativecommons.org/licenses/by-nc-sa/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Derechos de autor 2020 Javier Pedro Flores Arocutipa, Jorge Jinchuña Huallpa, Roberto Tito Condori Perez http://creativecommons.org/licenses/by-nc-sa/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf text/html |
dc.publisher.none.fl_str_mv |
Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables |
publisher.none.fl_str_mv |
Universidad Nacional Mayor de San Marcos, Facultad de Ciencias Contables |
dc.source.none.fl_str_mv |
Quipukamayoc; Vol 28 No 57 (2020); 17-23 Quipukamayoc; Vol. 28 Núm. 57 (2020); 17-23 1609-8196 1560-9103 reponame:Revista UNMSM - Quipukamayoc instname:Universidad Nacional Mayor de San Marcos instacron:UNMSM |
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Revista UNMSM - Quipukamayoc |
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Universidad Nacional Mayor de San Marcos |
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UNMSM |
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UNMSM |
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repository.mail.fl_str_mv |
mail@mail.com |
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13.882472 |
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