Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?

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The objective is to compare the mortality rates due to covid-19, between the poorest districts with the least poor districts, following the idea that the first ones would have the highest rates. To carry out this research, the poorest districts and the less poor districts were considered, for Metrop...

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Detalles Bibliográficos
Autores: Risco Franco, Carlos, Berenguel Tijero, Bruno
Formato: artículo
Fecha de Publicación:2023
Institución:Universidad Nacional de Ingeniería
Repositorio:Revistas - Universidad Nacional de Ingeniería
Lenguaje:español
inglés
OAI Identifier:oai:oai:revistas.uni.edu.pe:article/1872
Enlace del recurso:https://revistas.uni.edu.pe/index.php/iecos/article/view/1872
Nivel de acceso:acceso abierto
Materia:Distritos más pobres
covid19
tasa de mortalidad
Poorest districts
mortality rate
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spelling Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?Covid 19 en lima metropolitana y el callao: distritos más pobres, ¿los más afectados?Risco Franco, CarlosBerenguel Tijero, BrunoDistritos más pobrescovid19tasa de mortalidadPoorest districtscovid19mortality rateThe objective is to compare the mortality rates due to covid-19, between the poorest districts with the least poor districts, following the idea that the first ones would have the highest rates. To carry out this research, the poorest districts and the less poor districts were considered, for Metropolitan Lima and Callao, which were classified by the National Institute of Statistics and Informatics of Peru in 2018. Secondary information from the databases of the Ministry of Health and the National System of Deaths was used. The comparisons were made through the mortality rate due to covid-19, from March 2020 to December 2021. It was found that the mortality rate, due to covid-19, in most of the poorest districts was lower than that of less poor districts. It also turned out that, among the 7 districts of Metropolitan Lima with the highest mortality rates, no poorer district was found. In addition, a positive and significant correlation was found between the percentage of the population over 60 years of age in the districts of Metropolitan Lima and Callao and their respective mortality rates. Conclusion. In Metropolitan Lima and El Callao, the poorest districts, were not the most affected by covid-19, considering the mortality rate.El objetivo es comparar las tasas de mortalidad debido a la covid-19, entre los distritos más pobres con los distritos menos pobres, siguiendo la idea, que son los primeros los que tendrían las tasas más altas.  Para llevar adelante la presente investigación, se consideraron los distritos más pobres y los distritos menos pobres, para Lima Metropolitana y el Callao, que fueron clasificados por el Instituto Nacional de Estadística e Informática del Perú en el 2018. Se utilizó información secundaria de las bases de datos del Ministerio de Salud y del Sistema Nacional de Defunciones. Las comparaciones se hicieron a través de la tasa de mortalidad debido a la covid-19, desde marzo de 2020 a diciembre de 2021. Se encontró que la tasa de mortalidad, debido a la covid-19, en la mayoría de los distritos más pobres fue menor a la de los distritos menos pobres. También resultó que, entre los 7 distritos de Lima Metropolitana con las más altas tasas de mortalidad, no se encontró ningún distrito más pobre. Además, se halló una correlación positiva y significativa, entre el Porcentaje de población mayor a 60 años de los distritos de Lima Metropolitana y el Callao y sus respectivas tasas de mortalidad. Conclusion. En Lima Metropolitana y El Callao, los distritos más pobres, no fueron los más afectados por la covid-19, considerando la tasa de mortalidad.Universidad Nacional de Ingeniería2023-06-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPeer ReviewedEvaluado por paresapplication/pdftext/htmlaudio/mpegaudio/mpeghttps://revistas.uni.edu.pe/index.php/iecos/article/view/187210.21754/iecos.v24i1.1872revista IECOS; Vol. 24 No. 1 (2023); 102-115Revista IECOS; Vol. 24 Núm. 1 (2023); 102-1152788-74802961-284510.21754/iecos.v24i1reponame:Revistas - Universidad Nacional de Ingenieríainstname:Universidad Nacional de Ingenieríainstacron:UNIspaenghttps://revistas.uni.edu.pe/index.php/iecos/article/view/1872/2211https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/2248https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/3247https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/3248Derechos de autor 2023 Carlos Risco Franco, Bruno Berenguel Tijerohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:oai:revistas.uni.edu.pe:article/18722025-01-22T15:38:14Z
dc.title.none.fl_str_mv Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
Covid 19 en lima metropolitana y el callao: distritos más pobres, ¿los más afectados?
title Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
spellingShingle Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
Risco Franco, Carlos
Distritos más pobres
covid19
tasa de mortalidad
Poorest districts
covid19
mortality rate
title_short Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
title_full Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
title_fullStr Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
title_full_unstemmed Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
title_sort Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
dc.creator.none.fl_str_mv Risco Franco, Carlos
Berenguel Tijero, Bruno
author Risco Franco, Carlos
author_facet Risco Franco, Carlos
Berenguel Tijero, Bruno
author_role author
author2 Berenguel Tijero, Bruno
author2_role author
dc.subject.none.fl_str_mv Distritos más pobres
covid19
tasa de mortalidad
Poorest districts
covid19
mortality rate
topic Distritos más pobres
covid19
tasa de mortalidad
Poorest districts
covid19
mortality rate
description The objective is to compare the mortality rates due to covid-19, between the poorest districts with the least poor districts, following the idea that the first ones would have the highest rates. To carry out this research, the poorest districts and the less poor districts were considered, for Metropolitan Lima and Callao, which were classified by the National Institute of Statistics and Informatics of Peru in 2018. Secondary information from the databases of the Ministry of Health and the National System of Deaths was used. The comparisons were made through the mortality rate due to covid-19, from March 2020 to December 2021. It was found that the mortality rate, due to covid-19, in most of the poorest districts was lower than that of less poor districts. It also turned out that, among the 7 districts of Metropolitan Lima with the highest mortality rates, no poorer district was found. In addition, a positive and significant correlation was found between the percentage of the population over 60 years of age in the districts of Metropolitan Lima and Callao and their respective mortality rates. Conclusion. In Metropolitan Lima and El Callao, the poorest districts, were not the most affected by covid-19, considering the mortality rate.
publishDate 2023
dc.date.none.fl_str_mv 2023-06-30
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer Reviewed
Evaluado por pares
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1872
10.21754/iecos.v24i1.1872
url https://revistas.uni.edu.pe/index.php/iecos/article/view/1872
identifier_str_mv 10.21754/iecos.v24i1.1872
dc.language.none.fl_str_mv spa
eng
language spa
eng
dc.relation.none.fl_str_mv https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/2211
https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/2248
https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/3247
https://revistas.uni.edu.pe/index.php/iecos/article/view/1872/3248
dc.rights.none.fl_str_mv Derechos de autor 2023 Carlos Risco Franco, Bruno Berenguel Tijero
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Derechos de autor 2023 Carlos Risco Franco, Bruno Berenguel Tijero
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
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dc.publisher.none.fl_str_mv Universidad Nacional de Ingeniería
publisher.none.fl_str_mv Universidad Nacional de Ingeniería
dc.source.none.fl_str_mv revista IECOS; Vol. 24 No. 1 (2023); 102-115
Revista IECOS; Vol. 24 Núm. 1 (2023); 102-115
2788-7480
2961-2845
10.21754/iecos.v24i1
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