Short report J Epidemiol Community Health: first published as 10.1136/jech-2020-214724 on 2 April 2021. Downloaded from Social inequalities and the pandemic of COVID-19: the case of Rio de Janeiro Julio Silva ,1 Marcelo Ribeiro- Alves2 1Instituto Nacional de ABSTRACT the individual exposure risk is mediated solely by Infectologia Evandro Chagas Background The novel coronavirus (SARS-CoV -2) their ability to keep social distancing. This ability (INI), Fundação Oswaldo Cruz, Rio de Janeiro, Brazil is a global pandemic. The lack of protective vaccine can be, in turn, affected by material conditions and 2Laboratório de Pesquisa Clínica or treatment led most of the countries to follow the infrastructure of their households and neighbour- em DST- AIDS, Instituto Nacional flattening of the infection curve with social isolation hoods, for example, overcrowded households and de Infectologia Evandro Chagas measures. There is evidence that socioeconomic access to drinking water. Furthermore, the loss of (INI), Fundação Oswaldo Cruz, inequalities have been shaping the COVID-19 burden income due to business closures may disproportion- Rio de Janeiro, Brazil among low and middle- income countries. This study ately affect individuals who have informal jobs. In Correspondence to described what sociodemographic and socioeconomic their turn, COVID-19 susceptibility is influenced by Dr Julio Silva, Instituto Nacional factors were associated with the greatest risk of chronic comorbidities that follow a pattern moti- de Infectologia Evandro Chagas COVID-19 infection and mortality and how did the vated by social disparities (eg, household income, (INI), Fundação Oswaldo Cruz, importance of key neighbourhood-level socioeconomic occupation, education, wealth) that disproportion- Rio de Janeiro 21040-360, factors change over time during the early stages of the ately affects some segments of society (eg, people of Brazil; 5 julio. castro. alves. lima@ gmail. pandemic in the Rio de Janeiro municipality, Brazil. colour, immigrants). com Methods We linked socioeconomic attributes to The COVID-19 epidemic is already showing an confirmed cases and deaths from COVID-19 and unequal burden distribution among populations. Received 1 June 2020 computed age-standardised incidence and mortality rates For instance, Chen et al6 have evidenced a health Revised 4 March 2021 Accepted 11 March 2021 by domains such as age, gender, crowding, education, gradient in the New York municipality. They have income and race/ethnicity. shown that people from areas with over 20% of Results The evidence suggests that although age- households living in poverty conditions had a 44% standardised incidence rates were higher in wealthy more risk of being infected than people from areas neighbourhoods, age-standardised mortality rates were where households’ poverty conditions were less higher in deprived areas during the first 2 months of the than 5%. Similar risk disparities occurred in areas pandemic. The age- standardised mortality rates were with a majority of people of colour, a predominance also higher in males, and in areas with a predominance of low- income households and miserable quality of people of colour, which are disproportionately habitations (overcrowded households). In Scotland, represented in more vulnerable groups. The population people living in the most deprived areas were 2.3 also presented COVID-19 ’rejuvenation’, that is, people times more likely to die by COVID-19 than those became risk group younger than in developed countries. living in the least deprived ones.7 In England, the Conclusion We conclude that there is a strong health mortality rate was 55 deaths for 100 000 people in http://jech.bmj.com/ gradient for COVID-19 death risk during the early stages the most deprived areas, compared with 25 in the of the pandemic. COVID-19 cases continued to move wealthiest ones.8 Besides, men of colour were four towards the urban periphery and to more vulnerable times more likely to die by COVID-19 than white communities, threatening the health system functioning men.9 and increasing the health gradient. Latin America is the most unequal region in the world, and Brazil is one of the more unequal countries in terms of per capita income.10 During on October 1, 2021 by guest. Protected copyright. the first 2 months of the epidemic, Brazil had over INTRODUCTION 340 000 confirmed cases and 22 000 deaths from The novel coronavirus (SARS- CoV-2) that causes COVID-19, and Rio de Janeiro had over 20 161 the COVID-19 was identified in China in December confirmed cases and 2520 deaths. 2019.1 The virus had a high speed of transmis- This study’s objective is to describe what socio- sion by human- to- human contact. In places with demographic and socioeconomic factors were asso- health services, the case fatality rate varied around ciated with the greatest risk of COVID-19 infection © Author(s) (or their 1%–3%.2 The clinical evidence so far indicates that and mortality and how did the importance of key employer(s)) 2021. No the evolution towards a severe or critical infection is neighbourhood- level socioeconomic factors change commercial re- use. See rights more often in older adults and people with chronic and permissions. Published over time during the early stages of the pandemic in by BMJ. comorbidities, such as hypertension, diabetes, the Rio de Janeiro municipality, Brazil. cardiovascular- metabolic diseases and other respi- To cite: Silva J, ratory diseases.3 Globally, up to now, there were Ribeiro- Alves M. J Epidemiol over 107.38 million cases and 2.38 million deaths METHODS Community Health Epub 4 ahead of print: [please from COVID-19. Data include Day Month Year]. Socioeconomic inequalities can shape individuals’ We obtained publicly available data of COVID-19 doi:10.1136/jech-2020- exposure and susceptibility to COVID-19. Without at the individual level from the Brazilian Center of 214724 either a protective vaccine or effective treatment, Health Surveillance Strategic Information /Health Silva J, Ribeiro- Alves M. J Epidemiol Community Health 2021;0:1–5. doi:10.1136/jech-2020-214724 1 Short report J Epidemiol Community Health: first published as 10.1136/jech-2020-214724 on 2 April 2021. Downloaded from Ministry. The database contained individual-level information times higher, and the case fatality rate almost five times higher about notification date and age (aggregated by 20- year windows, than individuals aged 40–59 years. 0–19, 20–39, 40–59 and 60+), gender (women, men) and the All socioeconomic factors (crowding, education, income and neighbourhoods of only confirmed cases and deaths. Once race/ethnicity) were correlated with a higher age-standardised the available data about positive tested people for COVID-19 mortality rate, although the age-standardised incidence rate routinely did not include individual- level socioeconomic infor- showed the opposing or mixed trend depending on which socio- mation in health surveillance system data, we opted to link this economic factors were considered. Although cases were propor- information with socioeconomic census area in the most disag- tionately concentrated in wealthy neighbourhoods, the deaths gregated geographic level (neighbourhood level). We used the were frequently more observed in deprived areas. In more detail, geocoded health records to link them to socioeconomic attri- people living in high-income neighbourhoods (highest quartile) butes of Rio de Janeiro municipality imported from the Brazilian had 37% more risk to be infected than low-income ones (lowest Demographic Census 2010 data. Four conceptual domains were quartile), even though in low- income areas, they had 56% more considered relevant to characterising socioeconomic issues: risk to die (36.4 vs 57 per 100 000 persons). In neighbourhoods crowding (average number of bathrooms by the permanent with the predominance of people of colour (highest quartile), resident, measured as bathroom per person), education (% of there was 54% more risk to die (50.66 vs 32.92 per 100 000 illiteracy of neighbourhood residents from 10 to 14 years old), persons) than in neighbourhoods with the predominance of income (annual household per capita income as minimum wage white people (lowest quartile). This behaviour is similar if we fraction, 2010 R$510 current) and race/ethnicity (% of black or consider the neighbourhoods with the worst habitation quality brown self- declared neighbourhood residents). (overcrowded households) or lower educational levels of their residents. Statistical methodology Overall, considering death as the most undesirable health We computed crude and standardised incidence and mortality outcome, we found a strong gradient using COVID-19 death rates (per 100 000 people), calculated as the number of cases/ risk measures. These associations were not always monotonic deaths from COVID-19 by the total population exposed to the in statistical terms. All socioeconomic attributes presented some risk, respectively. Rates were standardised by age using the age monotonicity, although it was more robust for income and distribution of Rio de Janeiro municipality as reference. We crowding. If otherwise, we consider the probability of dying used the generalised linear Poisson model with the total popula- when infected, the health gradient is also consistent, and mono- tion (log10 transformed) as an offset to estimate relative ratios tonicity is even stronger than in the age- standardised mortality and CIs. We also estimated the case fatality rate, calculated