Socioeconomic Inequalities in COVID-19 Incidence During Different Epidemic Phases in South Korea

Abstract

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.

Health behaviors and the risk of COVID-19 incidence: A Bayesian hierarchical spatial analysis

“…W is constructed by , which is an inverse distance function with the exponents 2, where d ij is equal to the distance between municipality and [27] . The neighboring region of each municipality was defined based on whether the municipalities are located within distance, which did not have a spatial correlation in a variogram [28] . A variogram was generated based on the residual of the non-spatial null model, which did not have independent variables except offset variable (i.e., population in logarithmic scale).…”

Potential Epidemic Vulnerability and Socioepidemiological Profile of SARS-CoV2 in the Brazilian Northeast Region

“…Historically, disadvantaged people have been highly vulnerable to emerging infectious diseases, especially when they emerge as a persistent epidemic [17,18]. According to study [19], vulnerabilities related to income inequalities and health infrastructure were the ones that most shaped the dynamics of the first wave of COVID-19 in Brazil from March to October 2020.…”

“…Meanwhile, the second wave of the disease, which took place between November 2020 and June 2021, was influenced by the ideology and political orientation of municipalities that were focused on scientific denialism. In other countries, such as the US and China, low socioeconomic indicators were also associated with the distribution of COVID-19 incidence and lethality rates due to variations in personal hygiene, access to health care, and adherence to social distancing, and remote working recommendations [18,20].…”