Dataset Information

Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections.

ABSTRACT: 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.

SUBMITTER: Laajaj R

PROVIDER: S-EPMC9117199 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections.

Laajaj Rachid R Webb Duncan D Aristizabal Danilo D Behrentz Eduardo E Bernal Raquel R Buitrago Giancarlo G Cucunubá Zulma Z de la Hoz Fernando F Gaviria Alejandro A Hernández Luis Jorge LJ De Los Rios Camilo C Ramírez Varela Andrea A Restrepo Silvia S Schady Norbert N Vives Martha M

Scientific reports 20220518 1

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 inf ...[more]

PMID: 35585211

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Project description:ObjectiveArea-level socioeconomic status (SES) is associated with coronavirus disease 2019 (COVID-19) incidence. However, the underlying mechanism of the association is context-specific, and the choice of measure is still important. We aimed to evaluate the socioeconomic gradient regarding COVID-19 incidence in Korea based on several area-level SES measures.MethodsCOVID-19 incidence and area-level SES measures across 229 Korean municipalities were derived from various administrative regional data collected between 2015 and 2020. The Bayesian negative binomial model with a spatial autocorrelation term was used to estimate the incidence rate ratio (IRR) and relative index of inequality (RII) of each SES factor, with adjustment for covariates. The magnitude of association was compared between two epidemic phases: a low phase (<100 daily cases, from May 6 to August 14, 2020) and a rebound phase (>100 daily cases, from August 15 to December 31, 2020).ResultsArea-level socioeconomic inequalities in COVID-19 incidence between the most disadvantaged region and the least disadvantaged region were observed for nonemployment rates [RII = 1.40, 95% credible interval (Crl) = 1.01-1.95] and basic livelihood security recipients (RII = 2.66, 95% Crl = 1.12-5.97), but were not observed for other measures in the low phase. However, the magnitude of the inequalities of these SES variables diminished in the rebound phase. A higher area-level mobility showed a higher risk of COVID-19 incidence in both the low (IRR = 1.67, 95% Crl = 1.26-2.17) and rebound phases (IRR = 1.28, 95% Crl = 1.14-1.44). When SES and mobility measures were simultaneously adjusted, the association of SES with COVID-19 incidence remained significant but only in the low phase, indicating they were mutually independent in the low phase.ConclusionThe level of basic livelihood benefit recipients and nonemployment rate showed social stratification of COVID-19 incidence in Korea. Explanation of area-level inequalities in COVID-19 incidence may not be derived only from mobility differences in Korea but, instead, from the country's own context.

Dataset Information

Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections.

Publications

Understanding how socioeconomic inequalities drive inequalities in COVID-19 infections.

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