Social inequalities associated with COVID-19 case fatality rate in Fortaleza, Ceará state, Brazil, 2020**Article derived from the project entitled ‘Social inequalities during the COVID-19 pandemic in a metropolis of northeastern Brazil: an ecological study’, conceived by the ‘Grupo Cearense de Pesquisa em Doenças Infecciosas (GCPDI)’ of the Postgraduate Program in Public Health of the Federal University of Ceará in 2020.

Carlos Sanhueza-Sanzana Italo Wesley Oliveira Aguiar Rosa Lívia Freitas Almeida Carl Kendall Aminata Mendes Ligia Regina Franco Sansigolo Kerr About the authors

Abstract

Objective

To analyze the association among social and health inequalities, socioeconomic status, spatial segregation and Case Fatality Rate (CFR) due to COVID-19 in Fortaleza, the state capital of Ceará, Brazil.

Methods

This was an ecological study of confirmed cases and deaths due to COVID-19. The 119 neighborhoods of Fortaleza were used as units of analysis. Incidence, mortality and apparent CFR indicators due to COVID-19 were calculated between January 1 and June 8, 2020. Socioeconomic indicators were obtained from the 2010 Brazilian Demographic Census. Spatial analysis was performed and local and global Moran's indexes were calculated.

Results

There were 22,830 confirmed cases, 2,333 deaths and the apparent CFR was 12.7% (95% CI 11.6;13.9). Significant spatial autocorrelations between apparent CFR (I=0.35) and extreme poverty (I=0.51), overlapping in several neighborhoods of the city, were found.

Conclusion

The apparent CFR due to COVID-19 is associated with the worst socioeconomic and health status, which shows the relationship between social inequalities and health outcomes in times of pandemic.

Keywords:
SARS-CoV-2; Socioeconomic Factors; Social Inequity; Case Fatality Rate; Mortality; Spatial analysis

Introduction

The first pneumonia cases of unknown origin were identified in Wuhan, Hubei Province, China, in December, 2019. The pathogen has been identified as a novel enveloped RNA betacoronavirus, that has currently been named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the disease caused by this pathogen is called Coronavirus disease 2019 (COVID-19).11. Guan W-J, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020 Apr 30;382(18):1708-20. doi: https://doi.org/10.1056/NEJMoa2002032
https://doi.org/10.1056/NEJMoa2002032...
,22. Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med . 2020 Mar 26;382(13):1199-207. doi: https://doi.org/10.1056/NEJMoa2001316
https://doi.org/10.1056/NEJMoa2001316...
By February 4, 2021, the disease had caused 2,260,259 deaths of the 103,989,900 confirmed cases worldwide.33. World Health Organization. Situation by Region, country, territory & area [Internet]; 2021 [acesso 4 fev. 2021]. Disponível em: https://covid19.who.int/table
https://covid19.who.int/table...
Brazil was the world’s second leading country in terms of COVID-19 deaths, 225,099, with 9,229,322 confirmed cases and 24,591 new cases.44. Observatorio Fluminense. Covid-19 [Internet]. c2021 [acesso 4 fev. 2021]. Disponível em: https://www.covid19rj.org /
https://www.covid19rj.org...

Northeastern Brazil, one of the poorest regions in the country,55. Instituto Brasileiro de Geografia e Estatística (BR). Sinopse do censo demográfico 2010. Brasília, DF: IBGE, 2010 [acesso 3 jul. 2020]. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
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has been severely affected by the COVID-19 pandemic. By February 4, 2021, the region accounted for 23.6% of national cases and had the second highest incidence of new cases: 526.7 per 100,000 inhabitants.66. Instituto de Comunicação e Informação Cientifica e Tecnológica em Saúde (BR). Monitoramento Covid-19 [Internet]. 2021 [acesso 3 jul. 2020]. Disponível em: https://bigdata-covid19.icict.fiocruz.br /
https://bigdata-covid19.icict.fiocruz.br...
In Ceará, one of the nine states in the Northeast region, the first case was reported on March 15, 2020, with a COVID-19 incidence rate of 1,209.83 cases per 100,000 inhabitants. The state is second with the highest number of cumulative deaths: 94.2 per 100,000 inhabitants.44. Observatorio Fluminense. Covid-19 [Internet]. c2021 [acesso 4 fev. 2021]. Disponível em: https://www.covid19rj.org /
https://www.covid19rj.org...
,77. Cunha Júnior A, Castalão DHS, Matos D, Basilio J, Livosolo L, Grave M, et al. Relatório 8: progresso da Covid-19 no Brasil e no Estado do Rio de Janeiro: 26a semana epidemiológica [Internet]. Rio de Janeiro: Observatório Fluminense; 2020[acesso 3 jul. 2020]. doi: https://doi.org/10.12957/eduerj.covid19rj.relatorio8
https://doi.org/10.12957/eduerj.covid19r...

Fortaleza, the capital of Ceará, also experienced an increase in the number of deaths, which gained speed and lasted until mid-May, with an exponential increase in the daily average (36.6 deaths). Fortaleza was one of the most affected capitals in the country, following São Paulo and Rio de Janeiro.88. Ministerio da Saúde (BR), Secretaria de Vigilância Sanitária em Saúde, COE-COVID-19: semana epidemiológica 21 [Internet]. Brasília, DF: MS; 23 jun. 2020 [acesso 3 jul. 2020]. (Boletim Epidemiológico Especial, n. 17). Disponível em: https://antigo.saude.gov.br/images/pdf/2020/May/29/2020-05-25---BEE17---Boletim-do-COE.pdf
https://antigo.saude.gov.br/images/pdf/2...

Retrospective analyses of severe acute respiratory syndrome (SARS) cases, performed in laboratories, showed that in Ceará, there were cases of COVID-19 on January 1, 2020, shortly after the first official case had been reported by Wuhan authorities to the World Health Organization (WHO).99. Secretaria de Saúde (Ceará). Plataforma IntegraSUS: indicadores [sobre o novo Coronavirus (COVID-19)] [Internet]. [Ceará]: Secretaria de Saúde; 2020 [citado 3 jul. 2020]. Disponível em: https://integrasus.saude.ce.gov.br /
https://integrasus.saude.ce.gov.br...
,1010. Candido DS, Claro IM, Jesus JG, Souza WM, Moreira FRR, Dellicour S, et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Sience. 2020 Sep 4;369(6508):1255-60. doi: https://doi.org/10.1126/science.abd2161
https://doi.org/10.1126/science.abd2161...
It can be shown that, when the first case was identified, there had already been 1,303 cases reported in Fortaleza and two thirds of municipalities in the state had already cases of COVID-19.

Brazil is one of the most unequal countries in the world in terms of concentration of wealth. These inequalities have been determinants for the way the epidemic has spread around the country, making the poorest regions, such as the North and Northeast, respectively, those with the first and second highest prevalence of COVID-19 cases in the country.

The epidemic, both in Brazil and in the world, highlights the inequalities related to gender,1111. Wenham C, Smith J, Morgan R. COVID-19: the gendered impacts of the outbreak. Lancet. 2020;395(10227):846-8. doi: https://doi.org/10.1016/S0140-6736(20)30526-2
https://doi.org/10.1016/S0140-6736(20)30...
,1212. Alon T, Doepke M, Olmstead-Rumsey J, Tertil M. The impact of Covid-19 on gender equality. Cambrigde (MA): NMBER; 2020. (Working paper 26947). doi: https://doi.org/10.3386/w26947
https://doi.org/10.3386/w26947...
socioeconomic status1313. Chung RY-N, Dong D, Li MM. Socioeconomic gradient in health and the Covid-19. 2020 Apr 1; BMJ 369:m1329. doi: http://dx.doi.org/doi:10.1136/bmj.m1329
http://dx.doi.org/doi:10.1136/bmj.m1329...
and race or ethnicity.1414. Goes EF, Ramos DO, Ferreira AJF. Desigualdades raciais em saúde e a pandemia da Covid-19. Trab Educ Saude. 2020;18(3):e00278110. doi: https://doi.org/10.1590/1981-7746-sol00278.
https://doi.org/10.1590/1981-7746-sol002...
,1616. Laurencin CT, McClinton A. The Covid-19 pandemic: a call to action to identify and address racial and ethnic disparities. J Racial Ethn Heal Disparities. 2020;7(3):398-402. doi: https://doi.org/10.1007/s40615-020-00756-0
https://doi.org/10.1007/s40615-020-00756...
In general, in the country, there are knowledge gaps regarding transmission characteristics of COVID-19 in a context of great social inequality, with the population living in precarious housing and sanitation conditions, poor access to safe drinking water and in a situation of extreme crowding.1717. Werneck GL, Carvalho MS. A pandemia de Covid-19 no Brasil : crônica de uma crise sanitária anunciada. Cad Saude Publica. 2020;36(5):e00068820. doi: http://dx.doi.org/10.1590/0102-311X00068820
http://dx.doi.org/10.1590/0102-311X00068...

In order to understand how social inequalities influence health and risk production in the epidemic context, the objective of this study was to analyze the association among social inequalities related to health conditions, socioeconomic status, spatial segregation and apparent case fatality rate (CFR) due to COVID-19 in neighborhoods of the city of Fortaleza.

Methods

This was an ecological study, whose units of analysis were comprised of the 119 neighborhoods of the municipality of Fortaleza. The capital of the state of Ceará had an estimated population of 2,669,342 in 2020,55. Instituto Brasileiro de Geografia e Estatística (BR). Sinopse do censo demográfico 2010. Brasília, DF: IBGE, 2010 [acesso 3 jul. 2020]. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
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and the highest population density among all Brazilian capitals, 7,786.44 inhabitants per km2. According to data from the 2010 Brazilian Demographic Census, regarding social inequality, the city had a Gini coefficient of 0.62 and a large proportion of the population living in precarious conditions: 26% with inadequate sanitation, and a total of 508 favelas, home to 396,370 people, corresponding to 16% of the total population of the municipality which is 4% higher than the national average.55. Instituto Brasileiro de Geografia e Estatística (BR). Sinopse do censo demográfico 2010. Brasília, DF: IBGE, 2010 [acesso 3 jul. 2020]. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
https://biblioteca.ibge.gov.br/index.php...
,1818. Prefeitura de Fortaleza (CE). Prefeitura apresenta estudo sobre desenvolvimento humano por bairro em Fortaleza [Internet]. Fortaleza (CE): SDE; 2011 [acesso 3 jul. 2020]. Disponível em: https://pt.calameo.com/read/0032553521353dc27b3d9
https://pt.calameo.com/read/003255352135...

The study population was comprised of all positive and reported cases of COVID-19. Data of reported cases and laboratory test results were obtained from open data repositories, managed by the Government of the state of Ceará, related to reported and confirmed cases and deaths of the disease in Fortaleza, whose database was accessed on June 9, 2020 via the Integrated-health Information Platform of the Health Department of the state of Ceará.99. Secretaria de Saúde (Ceará). Plataforma IntegraSUS: indicadores [sobre o novo Coronavirus (COVID-19)] [Internet]. [Ceará]: Secretaria de Saúde; 2020 [citado 3 jul. 2020]. Disponível em: https://integrasus.saude.ce.gov.br /
https://integrasus.saude.ce.gov.br...
Data of reported cases between January 1 and June 8, 2020 were included, a total of 53,389 cases reported in the period, when mortality from COVID-19 in the municipality reached its first peak.99. Secretaria de Saúde (Ceará). Plataforma IntegraSUS: indicadores [sobre o novo Coronavirus (COVID-19)] [Internet]. [Ceará]: Secretaria de Saúde; 2020 [citado 3 jul. 2020]. Disponível em: https://integrasus.saude.ce.gov.br /
https://integrasus.saude.ce.gov.br...
Social and health indicators were obtained from the 2010 Brazilian Demographic Census.

The study variables included were:

  1. a) Individual

  2. - Sex (female; male);

  3. - Age group (in years: less than 1; 1 to 9; 10 to 19; 20 to 29; 30 to 39; 40 to 49; 50 to 59; 60 to 69; 70 or older);

  4. - Neighborhood of residence (by the name of the 119 neighborhoods of Fortaleza).

  5. These variables were used to characterize the cases and deaths analyzed.

  6. b) Aggregated by neighborhood

  7. 1) Epidemiological indicators

  8. - Number of cases confirmed by Reverse Transcription-Polymerase Chain Reaction (RT-PCR) and number of deaths due to COVID-19. Confirmed positive cases refer to cases that meet the case definition recommended by the WHO and the Ministry of Health: those investigated epidemiologically and laboratory-confirmed SARS-CoV-2 regardless of the case definition criteria (laboratory, epidemiological or clinical);

  9. - Number and types of comorbidities;

  10. - Calculation of epidemiological indicators: (i) covid-19 incidence rate was calculated from the number of confirmed cases, between January 1 and June 8, 2020, divided by the population of the neighborhoods multiplied by 10,000 inhabitants; (ii) cause-specific mortality rate due to COVID-19 was calculated by neighborhood, from the number of deaths divided by the population of the neighborhoods and multiplied by 10,000 inhabitants; and (iii) CFR due to COVID-19 was estimated by the ratio of the number of deaths by the total number of confirmed cases of COVID-19.

  11. 2) Socioeconomic status and sanitation conditions in the neighborhoods

  12. - Home ownership; households with access to proper sewage disposal; households with septic tanks; households with 2 or more bathrooms for exclusive use; households with elderly 65 years or older as the head of family; household with elderly (≥65 years old) who does not help with household expenses and is financially dependent; households with an illiterate person over 15 years of age; households with monthly income of less than 1 minimum wage; and households headed by women;

  13. - Median monthly family income per capita of households, in Reais (R$);

  14. - Median monthly income of women over 10 years of age, in Reais (R$).

  15. 3) Demographics

  16. - Households with elderly (≥65 years); households without water supply system; households without waste collection; households without access to electricity; households with more than 4 residents; and households in extreme poverty;

  17. - Infant mortality rate;55. Instituto Brasileiro de Geografia e Estatística (BR). Sinopse do censo demográfico 2010. Brasília, DF: IBGE, 2010 [acesso 3 jul. 2020]. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
    https://biblioteca.ibge.gov.br/index.php...

  18. - Average number of residents per household;

  19. - Human Development Index (HDI-B) by neighborhood, calculated by the Municipal Secretariat for Economic Development (SDE), Fortaleza, state of Ceará;1818. Prefeitura de Fortaleza (CE). Prefeitura apresenta estudo sobre desenvolvimento humano por bairro em Fortaleza [Internet]. Fortaleza (CE): SDE; 2011 [acesso 3 jul. 2020]. Disponível em: https://pt.calameo.com/read/0032553521353dc27b3d9
    https://pt.calameo.com/read/003255352135...

  20. - Population density (inhabitant/km2).

  21. 4) Spatial segregation indicator

  22. The socioeconomic index of the geographic context for health studies (GeoSES index), validated in Brazil, was used. The index is based on data from the 2010 Demographic Census to measure inequalities in health conditions at territorial levels, at three aggregation scales: national, Federative Unit and intra-municipal (neighborhoods). The GeoSES was developed using principal component analysis, starting with 41 variables, resulting in interval scores ranging from -1 (worst socioeconomic situation) to 1 (best socioeconomic situation). GeoSES constructs the socioeconomic status by considering seven parameters: education; poverty; wealth; income; segregation (education and income criteria); mobility; and lack of resources and services.1919. Barrozo LV, Fornaciali M, André CDS, Morais GAZ, Mansur G, Cabral-Miranda W, et al. GeoSES: A socioeconomic index for health and social research in Brazil. PLoS One. 2020 Apr 29;15(4):e0232074. doi: https://doi.org/10.1371/journal.pone.0232074
    https://doi.org/10.1371/journal.pone.023...

Descriptive statistics of relative frequencies of individual variables of confirmed cases and deaths due to COVID-19 were calculated by sex, age group and comorbidities, for the period during which the study was conducted. Numerical data were expressed as mean and standard deviation (SD), and in the absence of normal distribution, as median and interquartile range (25º-75º). The normal distribution of numerical variables was evaluated using the Shapiro-Wilk test. Count data were expressed as cases and percentages, presented with confidence intervals. The Moran index (I) was used as a measure of spatial autocorrelation in order to verify whether there is a spatially conditioned pattern by the epidemiological indicators of CFR, specific mortality and incidence of COVID-19, and socioeconomic, sanitation, sociodemographic and spatial segregation indicators. The first-order queen contiguity matrix (neighborhood) was used, at significant spatial pattern <5%. Local Indicators of Spatial Association (LISA) were also used to identify clusters in the municipality and their statistical significance, with graphical representation (LisaMap). Clusters were defined and thus presented as - high-high; low-low; high-low; low-high - scatterplots for socioeconomic, sociodemographic and spatial segregation variables that resulted statistically significant, <5%.

The organization, cleaning and descriptive analysis of data were performed using Stata software, version 16. Quantum Geographic Information System (QGIS), version 3.12.1, and GeoDa software, version 1.14.0, were used for spatial analysis.

Results

Between January 1, when the first confirmed case of COVID-19 was reported, and June 8, 2020, 22,830 confirmed cases and 2,333 deaths due to the disease were reported in the city of Fortaleza. There was a higher proportion of confirmed cases in women (54%); and deaths among men (57.4%) (Table 1).

Table 1
Absolute and relative frequencies of confirmed cases and deaths confirmed due to COVID-19, according to sex, age group and comorbidities, Fortaleza, Ceará, Brazil, January 1 - June 8, 2020

The majority of confirmed cases of COVID-19 were among the age group 40 to 59 (35.1%), followed by 30 to 39 (21.9%) and those aged 70 years or older (15.7%).

Deaths due to COVID-19 were concentrated in the age group over 60 years of age, which represented approximately 75% of all deaths, followed by 40 to 59 years of age (19.8%). There was also a lower number of deaths under 19 years of age, representing 0.5% of the total. Among the confirmed cases, a lower proportion of people with comorbidities, such as cardiovascular disease (5.3%) and diabetes mellitus (4.7%) was found, compared to fatal cases, of which 34.9% had cardiovascular disease and 31.9% had diabetes. Women’s and children’s health status also stood out: Fortaleza recorded 25 postpartum women with COVID-19, of these, 4 died (0.2%) (Table 1).

The incidence rate of confirmed COVID-19 cases in the municipality was 66.4(95%CI 59.2;73.6) per 10,000 inhabitants (Table 2). It was more concentrated in neighborhoods in northern and eastern zones of the city, the same neighborhoods showed the worst socioeconomic status and sanitation conditions, ranging from 76 to 236 cases per 10,000 inhabitants followed by neighborhoods in the northern and southern zones, with 54 to 75 cases per 10,000 inhabitants (Figure 1A).

Table 2
Epidemiological indicators of COVID-19 in neighborhoods of Fortaleza, Ceará, Brazil, January 1 - June 8, 2020

The city presented a specific mortality rate due to COVID-19 of 7.6(95%CI 6.8;8.5) per 10,000 inhabitants (Table 2). Among the neighborhoods that recorded higher mortality, there was a trend of concentration in those in the northern zone of the city, with rates ranging between 6.8 and 26.5 deaths per 10,000 inhabitants. It is worth pointing out the high mortality rate in the southern zone of the city, a region of high social vulnerability such as poverty, illiteracy and low income. Lower mortality rates - below 6.7 per 10,000 inhabitants. - were found in areas of the city where the population presented the highest income and most favorable sanitation conditions (Figure 1B).

Figure 1
Spatial distribution of deaths, apparent Case Fatality Rate (CFR), and mortality rates due to COVID-19, Fortaleza, Ceará, Brazil, January 1 - June 8, 2020

CFR due to COVID-19 in Fortaleza was 12.7% (95%CI 11.6;13.9), and the average of confirmed cases per neighborhood was 125.5 (95%CI 106.9;146.1), and the average of deaths per neighborhood was 16.1 (95%CI 13.4;18.6) (Table 2). The neighborhoods with the highest CFR (Figure 1C) also had the worst living conditions, presenting (i) a high percentage of households in poverty, (≥ 39%) (Figure 2A), (ii) low monthly income, up to R$ 600 (Figure 2B), (iii) a higher proportion of households headed by women, ranging from 31.2% to 36.8% (Figure 2C), (iv) a lower proportion of people aged 65 years or older (Figure 2D) and (v) a higher proportion of illiteracy, between 5.1% and 11.7% (Figures 2E-F).

The GeoSES index shows that the neighborhoods with the highest CFR were also those with higher proportions of poverty and the worst education level, household income and access to health services, ranging from -1 to -0.5 (Figure 2G).

Figure 2
Spatial distribution of socioeconomic indicators by neighborhoods of Fortaleza, Ceará, Brazil, 2010

The distribution of CFR due to COVID-19 according to the LISA clusters showed the existence of high-high statistically significant neighborhood clusters in the northwest region of the city (p-value<0.001), and low-low in neighborhoods in the eastern region (p-value<0.05) (Figure 3A). Regarding the proportion of households in poverty, there were also clusters of high-high neighborhoods in the northwest and low-low neighborhoods in the eastern region (Figure 3B). With regard to Moran’s index, CFR presented, and I value of 0.35 (Figure 3E), and 0.51 in the evaluation by households in poverty conditions (Figure 3F).

Figure 3
Spatial autocorrelation between apparent Case Fatality Rate (CFR) due to COVID-19 and extreme poverty, according to neighborhoods of Fortaleza, Ceará, Brazil, January 1 - June 8, 2020

Discussion

The results show a great disparity in the distribution of deaths due to COVID-19 in the neighborhoods of Fortaleza, demonstrating that the epidemic in the city disproportionately impacts the poorest populations. The unequal characteristics of the distribution and dispersion of SARS-CoV-2 in the city of Fortaleza show an unequal structure in risk exposure, strongly associated with social exclusion and precarious living conditions.2020. Instituto de Pesquisa e Estratégia Econômica do Ceará. Perfil municipal de Fortaleza: tema VIII: o mapa da extrema pobreza [Internet]. Fortaleza (CE): IPECE; out. 2012. [acesso 20 jul. 2020]. (Série informe, n. 43). Disponível em: https://www.ipece.ce.gov.br/wp-content/uploads/sites/45/2012/12/Ipece_Informe_43_05_novembro_2012.pdf
https://www.ipece.ce.gov.br/wp-content/u...
It is noteworthy the fact that there is a progressive dispersion of the epidemic, from areas with higher concentration of wealth to poorer neighborhoods.2121. Ministério da Saúde (BR). Doença pelo coronavírus Covid-19: Semana epidemiológica 24 [Internet]. Brasília, DF: MS ; 2020 [acesso 20 jul. 2020]. (Boletim epidemiológico especial, n. 18). Disponível em: http://antigo.saude.gov.br/images/pdf/2020/June/18/Boletim-epidemiologico-COVID-2.pdf
http://antigo.saude.gov.br/images/pdf/20...

Segregation by socioeconomic class and race/skin color is a strong determinant of health. Studies have shown that highly segregated African-American communities in the United States have been experiencing a disproportionate burden of mortality due to SARS-Cov-2 infection .1515. Kim SJ, Bostwick W. Social Vulnerability and Racial Inequality in Covid-19 Deaths in Chicago. Heal Educ Behav. 2020;47(4):509-13. doi: https://doi.org/10.1177/1090198120929677
https://doi.org/10.1177/1090198120929677...
,2222. Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King Jr. JT, Skanderson M, et al. Covid-19 by race and ethnicity: a national cohort study of 6 million United States veterans. medRxiv. Preprint 2020 May 17;. doi: https://doi.org/10.1101/2020.05.12.20099135
https://doi.org/10.1101/2020.05.12.20099...
These findings were similar to those identified in a study conducted in Rio de Janeiro.2323. Cavalcante JR, Abreu AJL. Covid-19 no município Rio de Janeiro: distribuição espacial dos primeiros casos e óbitos confirmados. Epidemiol Serv Saude. 2020;29(3):e2020204. doi: https://doi.org/10.5123/S1679-49742020000300007
https://doi.org/10.5123/S1679-4974202000...

Evidence from a population-based survey conducted in the city of Fortaleza in June 2020 found a seroprevalence of 14% and an estimated 370,000 people who developed antibodies to SARS-CoV-2.2424. Secretaria Municipal de Saúde. Inquérito soroprevalênca coronavírus em Fortaleza: dados preliminares [Internet]. Fortaleza (CE): SMS; 2020 [acesso 20 jul. 2020]. Disponível em: https://www.fortaleza.ce.gov.br/images/COVID_INQU%C3%89RITO_19062020.pdf
https://www.fortaleza.ce.gov.br/images/C...
However, most of the population was still susceptible to SARS-CoV-2 infection. According to the same research, among the neighborhoods most affected by COVID-19, those in the northwest region stood out - Barra do Ceará, Pirambu and Cristo Redentor - the prevalence was 20%, 3.5 fold higher than that in neighborhoods with the highest household income, showing health disparities. These results corroborate the findings of this study, which found high apparent CFR in these neighborhoods.

CFR due to COVID-19 reflects another pattern of social stratification: the highest proportion of households headed by low-income women, most of whom work in central areas of the city, in informal employment relationships, with greater exposure to the virus. This pattern could have favored the spread of the virus in the poorest neighborhoods, thus, justifying the high percentage of apparent CFR rate in low-income population - and greater poverty - living in these neighborhoods.

CFR due to COVID-19 also involves access to health care. In the areas with higher CFR, there is greater difficulty in accessing tertiary health care (of greater complexity), due to spatial segregation and distance to Primary Healthcare Centers (PHC).

The Brazilian case draws attention. The neoliberal political measures adopted aggravated the pandemic in Latin America.2525. Oliveira JF, Jorge DCP, Veiga RV, Rodrigues MS, Torquato MF, Silva NB, et al. Evaluating the burden of Covid-19 on hospital resources in Bahia, Brazil: a modelling-based analysis of 14.8 million individuals. medRxiv. Preprint 2020 . doi: https://doi.org/10.1101/2020.05.25.20105213
https://doi.org/10.1101/2020.05.25.20105...

26. Aquino EML, Silveira IH, Pescarini JM, Aquino R, Souza-Filho JA, Rocha AS, et al. Medidas de distanciamento social no controle da pandemia de Covid-19: potenciais impactos e desafios no Brasil. Cien Saude Colet. 2020;25(suppl 1):2423-46. doi: https://doi.org/10.1590/1413-81232020256.1.10502020
https://doi.org/10.1590/1413-81232020256...
-2727. Burki T. Covid-19 in Latin America. Lancet Infect Dis. 2020;20(5):547-8. doi: https://doi.org/10.1016/S1473-3099(20)30303-0
https://doi.org/10.1016/S1473-3099(20)30...
The country's recent experience with other epidemics - such as chikungunya fever, Zika fever, dengue fever and yellow fever - demonstrated the intersection between these infections and demographic, socioeconomic and health indicators of pockets of poverty, home to a significant proportion of the population.2828. Paixão ES, Teixeira MG, Rodrigues LC. Zika, chikungunya and dengue: the causes and threats of new and re-emerging arboviral diseases. BMC Glob Heath. 2018 Jan 4;3(Suppl 1):e000530. doi: https://doi.org/10.1136/bmjgh-2017-000530
https://doi.org/10.1136/bmjgh-2017-00053...

It is worth considering, among the limitations of this study, the fact that the demographic and socioeconomic variables used were obtained from the 2010 Demographic Census, and, therefore they may not correspond to the reality of 2020. However, data with the same level of disaggregation and reliability are not available, considering the lack of an updated demographic census.

It can be seen that, neighborhoods with high CFR due to COVID-19 also present precarious socioeconomic conditions, which are reflected in a high spatial segregation of the population, associated with the worst disease outcomes. Such conditions make it difficult a successful implementation of preventive measures. The population of these areas should have accessible testing and contact tracing, quarantine and physical distancing. In the medium and long term, it is crucial to implement policies to improve the general living conditions of the population, enhanced access to health care to prevent adverse effects of emerging and reemerging infectious diseases.

This study also presents some limitations related to the calculations performed for epidemiological indicators, given a considerable number of new cases and deaths due to COVID-19 underreported in the period during which the pandemic was being evaluated, in addition to the methods used in this analysis. The delay in the release of results and limited testing capacity for tracing infected individuals by health services in Fortaleza represent another bias for the emergence of different indicators in the real pandemic scenario in the city.

References

  • 1
    Guan W-J, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020 Apr 30;382(18):1708-20. doi: https://doi.org/10.1056/NEJMoa2002032
    » https://doi.org/10.1056/NEJMoa2002032
  • 2
    Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med . 2020 Mar 26;382(13):1199-207. doi: https://doi.org/10.1056/NEJMoa2001316
    » https://doi.org/10.1056/NEJMoa2001316
  • 3
    World Health Organization. Situation by Region, country, territory & area [Internet]; 2021 [acesso 4 fev. 2021]. Disponível em: https://covid19.who.int/table
    » https://covid19.who.int/table
  • 4
    Observatorio Fluminense. Covid-19 [Internet]. c2021 [acesso 4 fev. 2021]. Disponível em: https://www.covid19rj.org /
    » https://www.covid19rj.org
  • 5
    Instituto Brasileiro de Geografia e Estatística (BR). Sinopse do censo demográfico 2010. Brasília, DF: IBGE, 2010 [acesso 3 jul. 2020]. Disponível em: https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
    » https://biblioteca.ibge.gov.br/index.php/biblioteca-catalogo?view=detalhes&id=249230
  • 6
    Instituto de Comunicação e Informação Cientifica e Tecnológica em Saúde (BR). Monitoramento Covid-19 [Internet]. 2021 [acesso 3 jul. 2020]. Disponível em: https://bigdata-covid19.icict.fiocruz.br /
    » https://bigdata-covid19.icict.fiocruz.br
  • 7
    Cunha Júnior A, Castalão DHS, Matos D, Basilio J, Livosolo L, Grave M, et al. Relatório 8: progresso da Covid-19 no Brasil e no Estado do Rio de Janeiro: 26a semana epidemiológica [Internet]. Rio de Janeiro: Observatório Fluminense; 2020[acesso 3 jul. 2020]. doi: https://doi.org/10.12957/eduerj.covid19rj.relatorio8
    » https://doi.org/10.12957/eduerj.covid19rj.relatorio8
  • 8
    Ministerio da Saúde (BR), Secretaria de Vigilância Sanitária em Saúde, COE-COVID-19: semana epidemiológica 21 [Internet]. Brasília, DF: MS; 23 jun. 2020 [acesso 3 jul. 2020]. (Boletim Epidemiológico Especial, n. 17). Disponível em: https://antigo.saude.gov.br/images/pdf/2020/May/29/2020-05-25---BEE17---Boletim-do-COE.pdf
    » https://antigo.saude.gov.br/images/pdf/2020/May/29/2020-05-25---BEE17---Boletim-do-COE.pdf
  • 9
    Secretaria de Saúde (Ceará). Plataforma IntegraSUS: indicadores [sobre o novo Coronavirus (COVID-19)] [Internet]. [Ceará]: Secretaria de Saúde; 2020 [citado 3 jul. 2020]. Disponível em: https://integrasus.saude.ce.gov.br /
    » https://integrasus.saude.ce.gov.br
  • 10
    Candido DS, Claro IM, Jesus JG, Souza WM, Moreira FRR, Dellicour S, et al. Evolution and epidemic spread of SARS-CoV-2 in Brazil. Sience. 2020 Sep 4;369(6508):1255-60. doi: https://doi.org/10.1126/science.abd2161
    » https://doi.org/10.1126/science.abd2161
  • 11
    Wenham C, Smith J, Morgan R. COVID-19: the gendered impacts of the outbreak. Lancet. 2020;395(10227):846-8. doi: https://doi.org/10.1016/S0140-6736(20)30526-2
    » https://doi.org/10.1016/S0140-6736(20)30526-2
  • 12
    Alon T, Doepke M, Olmstead-Rumsey J, Tertil M. The impact of Covid-19 on gender equality. Cambrigde (MA): NMBER; 2020. (Working paper 26947). doi: https://doi.org/10.3386/w26947
    » https://doi.org/10.3386/w26947
  • 13
    Chung RY-N, Dong D, Li MM. Socioeconomic gradient in health and the Covid-19. 2020 Apr 1; BMJ 369:m1329. doi: http://dx.doi.org/doi:10.1136/bmj.m1329
    » http://dx.doi.org/doi:10.1136/bmj.m1329
  • 14
    Goes EF, Ramos DO, Ferreira AJF. Desigualdades raciais em saúde e a pandemia da Covid-19. Trab Educ Saude. 2020;18(3):e00278110. doi: https://doi.org/10.1590/1981-7746-sol00278.
    » https://doi.org/10.1590/1981-7746-sol00278
  • 15
    Kim SJ, Bostwick W. Social Vulnerability and Racial Inequality in Covid-19 Deaths in Chicago. Heal Educ Behav. 2020;47(4):509-13. doi: https://doi.org/10.1177/1090198120929677
    » https://doi.org/10.1177/1090198120929677
  • 16
    Laurencin CT, McClinton A. The Covid-19 pandemic: a call to action to identify and address racial and ethnic disparities. J Racial Ethn Heal Disparities. 2020;7(3):398-402. doi: https://doi.org/10.1007/s40615-020-00756-0
    » https://doi.org/10.1007/s40615-020-00756-0
  • 17
    Werneck GL, Carvalho MS. A pandemia de Covid-19 no Brasil : crônica de uma crise sanitária anunciada. Cad Saude Publica. 2020;36(5):e00068820. doi: http://dx.doi.org/10.1590/0102-311X00068820
    » http://dx.doi.org/10.1590/0102-311X00068820
  • 18
    Prefeitura de Fortaleza (CE). Prefeitura apresenta estudo sobre desenvolvimento humano por bairro em Fortaleza [Internet]. Fortaleza (CE): SDE; 2011 [acesso 3 jul. 2020]. Disponível em: https://pt.calameo.com/read/0032553521353dc27b3d9
    » https://pt.calameo.com/read/0032553521353dc27b3d9
  • 19
    Barrozo LV, Fornaciali M, André CDS, Morais GAZ, Mansur G, Cabral-Miranda W, et al. GeoSES: A socioeconomic index for health and social research in Brazil. PLoS One. 2020 Apr 29;15(4):e0232074. doi: https://doi.org/10.1371/journal.pone.0232074
    » https://doi.org/10.1371/journal.pone.0232074
  • 20
    Instituto de Pesquisa e Estratégia Econômica do Ceará. Perfil municipal de Fortaleza: tema VIII: o mapa da extrema pobreza [Internet]. Fortaleza (CE): IPECE; out. 2012. [acesso 20 jul. 2020]. (Série informe, n. 43). Disponível em: https://www.ipece.ce.gov.br/wp-content/uploads/sites/45/2012/12/Ipece_Informe_43_05_novembro_2012.pdf
    » https://www.ipece.ce.gov.br/wp-content/uploads/sites/45/2012/12/Ipece_Informe_43_05_novembro_2012.pdf
  • 21
    Ministério da Saúde (BR). Doença pelo coronavírus Covid-19: Semana epidemiológica 24 [Internet]. Brasília, DF: MS ; 2020 [acesso 20 jul. 2020]. (Boletim epidemiológico especial, n. 18). Disponível em: http://antigo.saude.gov.br/images/pdf/2020/June/18/Boletim-epidemiologico-COVID-2.pdf
    » http://antigo.saude.gov.br/images/pdf/2020/June/18/Boletim-epidemiologico-COVID-2.pdf
  • 22
    Rentsch CT, Kidwai-Khan F, Tate JP, Park LS, King Jr. JT, Skanderson M, et al. Covid-19 by race and ethnicity: a national cohort study of 6 million United States veterans. medRxiv. Preprint 2020 May 17;. doi: https://doi.org/10.1101/2020.05.12.20099135
    » https://doi.org/10.1101/2020.05.12.20099135
  • 23
    Cavalcante JR, Abreu AJL. Covid-19 no município Rio de Janeiro: distribuição espacial dos primeiros casos e óbitos confirmados. Epidemiol Serv Saude. 2020;29(3):e2020204. doi: https://doi.org/10.5123/S1679-49742020000300007
    » https://doi.org/10.5123/S1679-49742020000300007
  • 24
    Secretaria Municipal de Saúde. Inquérito soroprevalênca coronavírus em Fortaleza: dados preliminares [Internet]. Fortaleza (CE): SMS; 2020 [acesso 20 jul. 2020]. Disponível em: https://www.fortaleza.ce.gov.br/images/COVID_INQU%C3%89RITO_19062020.pdf
    » https://www.fortaleza.ce.gov.br/images/COVID_INQU%C3%89RITO_19062020.pdf
  • 25
    Oliveira JF, Jorge DCP, Veiga RV, Rodrigues MS, Torquato MF, Silva NB, et al. Evaluating the burden of Covid-19 on hospital resources in Bahia, Brazil: a modelling-based analysis of 14.8 million individuals. medRxiv. Preprint 2020 . doi: https://doi.org/10.1101/2020.05.25.20105213
    » https://doi.org/10.1101/2020.05.25.20105213
  • 26
    Aquino EML, Silveira IH, Pescarini JM, Aquino R, Souza-Filho JA, Rocha AS, et al. Medidas de distanciamento social no controle da pandemia de Covid-19: potenciais impactos e desafios no Brasil. Cien Saude Colet. 2020;25(suppl 1):2423-46. doi: https://doi.org/10.1590/1413-81232020256.1.10502020
    » https://doi.org/10.1590/1413-81232020256.1.10502020
  • 27
    Burki T. Covid-19 in Latin America. Lancet Infect Dis. 2020;20(5):547-8. doi: https://doi.org/10.1016/S1473-3099(20)30303-0
    » https://doi.org/10.1016/S1473-3099(20)30303-0
  • 28
    Paixão ES, Teixeira MG, Rodrigues LC. Zika, chikungunya and dengue: the causes and threats of new and re-emerging arboviral diseases. BMC Glob Heath. 2018 Jan 4;3(Suppl 1):e000530. doi: https://doi.org/10.1136/bmjgh-2017-000530
    » https://doi.org/10.1136/bmjgh-2017-000530

  • *
    Article derived from the project entitled ‘Social inequalities during the COVID-19 pandemic in a metropolis of northeastern Brazil: an ecological study’, conceived by the ‘Grupo Cearense de Pesquisa em Doenças Infecciosas (GCPDI)’ of the Postgraduate Program in Public Health of the Federal University of Ceará in 2020.

Publication Dates

  • Publication in this collection
    20 Aug 2021
  • Date of issue
    2021

History

  • Received
    11 Sept 2020
  • Accepted
    01 Apr 2021
Secretaria de Vigilância em Saúde - Ministério da Saúde do Brasil Brasília - Distrito Federal - Brazil
E-mail: leilapgarcia@gmail.com