Effect of income on the cumulative incidence of COVID-19: an ecological study

Abstract

<jats:p> Objective to analyze the relationship between per capita income and the cumulative incidence of COVID-19 in the neighborhoods of the city of Rio de Janeiro, RJ, Brazil. Method an ecological study using neighborhoods as units of analysis. The cumulative incidence rate per 100,000 inhabitants and the median of potential confounding variables (sex, race, and age) were calculated. Multiple analysis included quantile regression, estimating the regression coefficients of the variable income for every five percentiles from the 10th to 90th percentiles to verify the relationship between income and incidence. Results the city’s rate was 36.58 new cases per 100,000 inhabitants. In general, the highest rates were observed in the wealthiest regions. Multiple analysis was consistent with this observation since the per capita income affected all percentiles analyzed, with a median regression coefficient of 0.02 (p-value &lt;0.001; R2 32.93). That is, there is an increase of R$ 0.02 in the neighborhood’s per capita income for every unit of incidence. Conclusion cumulative incident rates of COVID-19 are influenced by one’s neighborhood of residency, suggesting that access to testing is uneven.</jats:p>

Epidemiological and clinical characteristics of the first 557 successive patients with COVID-19 in Pernambuco state, Northeast Brazil

“…1 B, the first SARS-CoV-2 cases were concentrated in neighborhoods with a higher nominal monthly household income, such as the Rosarinho, Espinheiro, and Boa Viagem neighborhoods that had average earnings above 10 Brazilian minimum wages. Our data is in agreement with a study done in Rio de Janeiro, Brazil in which the highest rates of COVID-19 were observed in the wealthiest regions [ 12 ].…”

Ecologic association between influenza and COVID-19 mortality rates in European countries

“…For example, age structure explained part of the between-country differences in COVID-19 mortality and case-fatality rates [4,20]; median prevalence of the five conditions most frequently associated with severe COVID-19 in USA allowed to identify the areas at highest risk for COVID-19 death [21]; age-specific prevalence of comorbidities explained the differences in mortality between Nigeria, Brazil and Italy [22]. Economic and healthcare associated variables are other aggregated data potentially useful to predict COVID-19 severity and spread [68][69][70], as well as inequalities within the general population [71]. Unlike these studies, however, the present analysis considered the mortality rate from an infectious disease that was not somewhat causally associated with COVID-19 mortality and death and was based on a different assumption, namely, that the two diseases shared a set of determinants, ranging from the characteristics of the population at highest risk, to transmission routes, from case and death misclassifications, to the efficiency of the healthcare systems.…”

Padrões de ocorrência do COVID-19 nos municípios da Região Metropolitana do Rio de Janeiro e a vulnerabilidade social

“…Em São Paulo, dados publicado pela Secretaria Municipal de Saúde em 17/04/2020 apontavam maior incidência em bairros mais ricos (rede Brasil, 2020 3), situação diferente à encontrada em final de julho, quando um inquérito sorológico mostrou que a população que tem mais risco de contrair a infecção pelo SARS-CoV-2 é de cor preta e parda, menor instrução e menor renda mensal. Na cidade do Rio de Janeiro os primeiros casos se concentraram em áreas mais ricas e em bairros Development, v. 9, n. 10, e919108454, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i10.8454 de maior renda per capita (Cavalcante et al, 2020, Rafael et al, 2020. A associação positiva entre incidência da doença e fatores sócio econômicos, em estudos ecológicos, também foi observada a nível de países com dados até maio de 2020.…”

“…Outros estudos indicam que a incidência foi maior em afrodescendentes e latinos, por esses grupos serem os mais representados nas áreas essenciais, ou nos empregos temporários, ou ainda tinham maiores dificuldades de praticar o distanciamento social por causa de suas condições de moradia (Chen et al, 2020;Thebault et al, 2020). Research, Society and Development, v. 9, n. 10, e919108454, 2020 (CC BY 4.0) | ISSN 2525-3409 | DOI: http://dx.doi.org/10.33448/rsd-v9i10.8454 6 A situação observada nos grandes centros urbanos brasileiros, entre eles o município do Rio de |Janeiro, no início da epidemia, foi diferente uma vez que os primeiros casos foram de pessoas que tinham viajado ao exterior e se concentravam em áreas mais privilegiadas (Cavalcante et al, 2020;Rafael et al, 2020). A distribuição desigual dos testes também foi citada como possível causa para a menor incidência de casos notificados em áreas desfavorecidas.…”