Congenital Syphilis in Brazil: Municipal Antenatal Care, Primary Health Care Capacity, and Territorial Inequalities, 2015-2024.

Objectives

To describe spatial patterns of gestational (GS) and congenital syphilis (CS) in Brazil and assess municipal antenatal care, sociodemographic, and primary-care correlates of CS notifications after accounting for GS burden.

Methods

We conducted a nationwide ecological study using routinely collected SINAN, SINASC, and CNES data (2015-2024). Spatial analyses used empirical Bayes smoothing, Global Moran's I, and LISA. Associations were estimated with a Bayesian negative-binomial spatiotemporal model including municipal random effects, annually replicated Besag fields, a first-order random walk, and an estimated coefficient for GS burden. Sensitivity analyses evaluated formulations, adjacency, priors, and age composition.

Results

Spatial analyses included 55,699 municipality-years from 5,570 municipalities; the primary model included 28,436 observations from 3,625 municipalities. CS showed recurrent high-high clusters in the North and Northeast. Per 10-percentage-point increase, fewer than seven antenatal visits (adjusted ratio 1.10, 95% CrI 1.08-1.11) and births to women recorded as Black or Brown (1.07, 1.06-1.08) were positively associated with expected CS notifications, whereas low maternal education was inversely associated (0.93, 0.92-0.95). Each additional registered Family Health Strategy team per 10,000 population was inversely associated (0.89, 0.87-0.91), although this estimate was model-sensitive. GS elasticity was 0.72 (0.71-0.74); estimates were stable under KNN-5.

Conclusions

FOR PRACTICE CS remained spatially concentrated, and municipal antenatal-care utilization, sociodemographic composition, and primary-care capacity were associated with expected CS notifications after accounting for GS burden. These ecological findings may help identify territories where care delivery, primary-care capacity, and surveillance warrant closer assessment. They do not estimate individual transmission risk or establish causal effects.