Show simple item record

dc.rights.licenseAl consultar y hacer uso de este recurso, está aceptando las condiciones de uso establecidas por los autores.spa
dc.contributor.authorLaajaj, Rachid
dc.contributor.authorWebb, Duncan
dc.contributor.authorAristizabal, Danilo
dc.contributor.authorBehrentz, Eduardo
dc.contributor.authorBernal, Raquel
dc.contributor.authorBuitrago, Giancarlo
dc.contributor.authorCucunubá, Zulma
dc.contributor.authorde la Hoz, Fernando
dc.contributor.authorGaviria, Alejandro
dc.contributor.authorHernández, Luis Jorge
dc.contributor.authorDe Los Rios, Camilo
dc.contributor.authorRamírez Varela, Andrea
dc.contributor.authorRestrepo, Silvia
dc.contributor.authorSchady, Norbert
dc.contributor.authorVives, Martha
dc.date.accessioned2021-05-05T21:36:50Z
dc.date.available2021-05-05T21:36:50Z
dc.date.issued2021
dc.identifier.urihttp://hdl.handle.net/1992/49961
dc.description.abstractAcross the world, the SARS-CoV-2 (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 inability 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. Interventions that mitigate transmission are often more effective when targeted on socioeconomically disadvantaged groups.
dc.formatapplication/pdf
dc.format.extent56 páginas
dc.language.isoeng
dc.publisherUniversidad de los Andes, Facultad de Economía, CEDE
dc.relation.ispartofseriesDocumentos CEDE No. 24 Abril de 2021
dc.titleUnderstanding how socioeconomic inequalities drive inequalities in SARS-CoV-2 infections
dc.typeDocumento de trabajospa
dc.identifier.eissn1657-7191
dc.subject.keywordCOVID-19
dc.subject.keywordInequality
dc.subject.keywordInfections
dc.subject.keywordSocioeconomic strata
dc.type.driverinfo:eu-repo/semantics/workingPaperspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
dc.provenance.unitFacultad de Economía
dc.subject.jelI14, I15, I18, O54
dc.identifier.instnameinstname:Universidad de los Andesspa
dc.identifier.reponamereponame:Repositorio Institucional Sénecaspa
dc.identifier.repourlrepourl:https://repositorio.uniandes.edu.co/spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.type.coarhttp://purl.org/coar/resource_type/c_8042spa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.type.contentTextspa
dc.type.redcolhttps://purl.org/redcol/resource_type/WPspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


Files in this item

Thumbnail

Name: dcede2021-24.pdf

This item appears in the following Collection(s)

Show simple item record