Covid 19 in metropolitan Lima and Callao: poorest districts, the most affected?
Descripción del Articulo
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...
| Autores: | , |
|---|---|
| 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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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 |
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openAccess |
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application/pdf text/html audio/mpeg audio/mpeg |
| dc.publisher.none.fl_str_mv |
Universidad Nacional de Ingeniería |
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Universidad Nacional de Ingeniería |
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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 reponame:Revistas - Universidad Nacional de Ingeniería instname:Universidad Nacional de Ingeniería instacron:UNI |
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La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).