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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...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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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. |
format | Online Article Text |
id | pubmed-9117199 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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