Determinants of congenital syphilis in Fortaleza, Brazil: A retrospective case-control study.

Congenital syphilis (CS) is a significant public health problem in Brazil. Despite efforts to increase syphilis testing and treatment among pregnant women, rates of CS in the country remain high. We conducted a retrospective case-control study to identify potential associations between the mothers' sociodemographic characteristics, clinical factors related to the current and previous pregnancies, and the occurrence of CS among newborns in Fortaleza, a populous city with one of the highest incidences of CS in Brazil. Data from newborns diagnosed with CS between 2017 and 2020 were extracted from SINAN, the national database for notifiable diseases. Data from women who had delivered an infant with CS were extracted from SINASC, the national database for registration of live births, and linked with their infant's data. CS cases and non-CS controls were matched by year of birth at a ratio of 1:3 respectively. Potential associations were estimated using a multivariate regression model accounting for sociodemographic, obstetric, and antenatal care-related factors. Epidemiological data from 8,744 live births were included in the analysis, including 2,186 cases and 6,588 controls. The final multivariate regression model identified increased odds of delivering an infant with CS among pregnant women and girls aged below 20 years (OR 1.29), single women (OR 1.48), women who had less than 8 years of formal education (OR 2.42), women who delivered in a public hospital (OR 6.92), women who had more than 4 previous pregnancies (OR 1.60), and women who had one or more prior fetal loss (OR 1.19). The odds of delivering an infant with CS also increased as the number of antenatal visits decreased. Women who did not attend any antenatal visits had 3.94 times the odds of delivering an infant with CS compared to women who attended 7 or more visits. Our study found that increased odds of delivering an infant with CS were highly associated with factors related to socioeconomic vulnerability. These determinants not only affect the access to essential antenatal care services, but also the continuity and quality of such preventive measures. Future policies aimed at reducing the incidence of CS should not only target those pregnant women and adolescents with identifiable risk factors for testing, but also assure high quality care, treatment and follow-up for this group.

Decomposition of socioeconomic inequalities in arboviral diseases in Brazil and Colombia (2007-2017).

BACKGROUND: We used surveillance data from Brazil and Colombia during 2007-2017 to assess the presence of socioeconomic inequalities on dengue, chikungunya and Zika at the neighborhood level in two Latin American cities. METHODS: To quantify the inequality, we estimated and decomposed the relative concentration index of inequality (RCI) accounting for the spatiotemporal distribution of the diseases. RESULTS: There were 281 426 arboviral cases notified in Fortaleza, Brazil, and 40 889 in Medellin, Colombia. The RCI indicated greater concentration of dengue cases among people living in low socioeconomic settings in both sites. The RCIs for chikungunya in Fortaleza covered the line of equality during their introduction in 2014, while the RCIs for Zika and chikungunya in Medellin indicated the presence of a small inequality. The RCI decomposition showed that year of notification and age were the main contributors to this inequality. In Medellin, the RCI decomposition showed that age and access to waste management accounted for 75.5%, 72.2% and 54.5% of the overall inequality towards the poor for dengue, chikungunya and Zika, respectively. CONCLUSIONS: Our study presents estimates of the socioeconomic inequality of arboviruses and its decomposition in two Latin American cities. We corroborate the concentration of arboviral diseases in low socioeconomic neighborhoods and identify that year of occurrence, age, presence of healthcare facilities and waste management are key determinants of the heterogenous distribution of endemic arboviruses across the socioeconomic spectrum.

Spatiotemporal distribution and socioeconomic disparities of dengue, chikungunya and Zika in two Latin American cities from 2007 to 2017.

OBJECTIVE: To assess the presence, pattern and magnitude of socioeconomic inequalities on dengue, chikungunya and Zika in Latin America, accounting for their spatiotemporal distribution. METHODS: Using longitudinal surveillance data (reported arboviruses) from Fortaleza, Brazil and Medellin, Colombia (2007-2017), we fit Bayesian hierarchical models with structured random effects to estimate: (i) spatiotemporally adjusted incidence rates; (ii) Relative Concentration Index and Absolute Concentration Index of inequality; (iii) temporal trends in RCIs; and (iv) socioeconomic-specific estimates of disease distribution. The spatial analysis was conducted at the neighbourhood level (urban settings). The socioeconomic measures were the median monthly household income (MMHI) for Brazil and the Socio-Economic Strata index (SES) in Colombia. RESULTS: There were 281 426 notified arboviral cases in Fortaleza and 40 887 in Medellin. We observed greater concentration of dengue among residents of low socioeconomic neighbourhoods in both cities: Relative Concentration Index = -0.12 (95% CI = -0.13, -0.10) in Fortaleza and Relative Concentration Index = -0.04 (95% CI = -0.05, -0.03) in Medellin. The magnitude of inequalities varied over time across sites and was larger during outbreaks. We identified a non-monotonic association between disease rates and socioeconomic measures, especially for chikungunya, that changed over time. The Relative Concentration Index and Absolute Concentration Index showed few if any inequalities for Zika. The socioeconomic-specific model showed increased disease rates at MMHI below US$400 in Brazil and at SES-index below level four, in Colombia. CONCLUSIONS: We provide robust quantitative estimates of socioeconomic inequalities in arboviruses for two Latin American cities. Our findings could inform policymaking by identifying spatial hotspots for arboviruses and targeting strategies to decrease disparities at the local level.