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Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections

Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mech...

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Autores principales: Laajaj, Rachid, Webb, Duncan, Aristizabal, Danilo, Behrentz, Eduardo, Bernal, Raquel, Buitrago, Giancarlo, Cucunubá, Zulma, de la Hoz, Fernando, Gaviria, Alejandro, Hernández, Luis Jorge, De Los Rios, Camilo, Ramírez Varela, Andrea, Restrepo, Silvia, Schady, Norbert, Vives, Martha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117199/
https://www.ncbi.nlm.nih.gov/pubmed/35585211
http://dx.doi.org/10.1038/s41598-022-11706-7
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author Laajaj, Rachid
Webb, Duncan
Aristizabal, Danilo
Behrentz, Eduardo
Bernal, Raquel
Buitrago, Giancarlo
Cucunubá, Zulma
de la Hoz, Fernando
Gaviria, Alejandro
Hernández, Luis Jorge
De Los Rios, Camilo
Ramírez Varela, Andrea
Restrepo, Silvia
Schady, Norbert
Vives, Martha
author_facet Laajaj, Rachid
Webb, Duncan
Aristizabal, Danilo
Behrentz, Eduardo
Bernal, Raquel
Buitrago, Giancarlo
Cucunubá, Zulma
de la Hoz, Fernando
Gaviria, Alejandro
Hernández, Luis Jorge
De Los Rios, Camilo
Ramírez Varela, Andrea
Restrepo, Silvia
Schady, Norbert
Vives, Martha
author_sort Laajaj, Rachid
collection PubMed
description Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mechanisms best explain the disproportionate impact of the virus on the poor. Combining an epidemiological model with rich data from Bogotá, Colombia, we show that total infections and inequalities in infections are largely driven by inequalities in the ability to work remotely and in within-home secondary attack rates. Inequalities in isolation behavior are less important but non-negligible, while access to testing and contract-tracing plays practically no role because it is too slow to contain the virus. Interventions that mitigate transmission are often more effective when targeted on socioeconomically disadvantaged groups.
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spelling pubmed-91171992022-05-20 Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections Laajaj, Rachid Webb, Duncan Aristizabal, Danilo Behrentz, Eduardo Bernal, Raquel Buitrago, Giancarlo Cucunubá, Zulma de la Hoz, Fernando Gaviria, Alejandro Hernández, Luis Jorge De Los Rios, Camilo Ramírez Varela, Andrea Restrepo, Silvia Schady, Norbert Vives, Martha Sci Rep Article Across the world, the COVID-19 pandemic has disproportionately affected economically disadvantaged groups. This differential impact has numerous possible explanations, each with significantly different policy implications. We examine, for the first time in a low- or middle-income country, which mechanisms best explain the disproportionate impact of the virus on the poor. Combining an epidemiological model with rich data from Bogotá, Colombia, we show that total infections and inequalities in infections are largely driven by inequalities in the ability to work remotely and in within-home secondary attack rates. Inequalities in isolation behavior are less important but non-negligible, while access to testing and contract-tracing plays practically no role because it is too slow to contain the virus. Interventions that mitigate transmission are often more effective when targeted on socioeconomically disadvantaged groups. Nature Publishing Group UK 2022-05-18 /pmc/articles/PMC9117199/ /pubmed/35585211 http://dx.doi.org/10.1038/s41598-022-11706-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Laajaj, Rachid
Webb, Duncan
Aristizabal, Danilo
Behrentz, Eduardo
Bernal, Raquel
Buitrago, Giancarlo
Cucunubá, Zulma
de la Hoz, Fernando
Gaviria, Alejandro
Hernández, Luis Jorge
De Los Rios, Camilo
Ramírez Varela, Andrea
Restrepo, Silvia
Schady, Norbert
Vives, Martha
Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title_full Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title_fullStr Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title_full_unstemmed Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title_short Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections
title_sort understanding how socioeconomic inequalities drive inequalities in covid-19 infections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117199/
https://www.ncbi.nlm.nih.gov/pubmed/35585211
http://dx.doi.org/10.1038/s41598-022-11706-7
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