Epidemiology and Spatiotemporal Patterns of Leprosy Detection in the State of Bahia, Brazilian Northeast Region, 2001⁻2014

Abstract

The detection of leprosy cases is distributed unequally in Brazil, with high-risk clusters mainly in the North and Northeast regions. Knowledge on epidemiology and spatiotemporal patterns of leprosy occurrence and late diagnosis in these areas is critical to improve control measures. We performed a study including all leprosy cases notified in the 417 municipalities of Bahia state, from 2001 to 2014. New case detection (overall and pediatric <15 years) and grade 2 disability (G2D) rates were calculated and stratified according to socio-demographic variables. Spatial analyses were performed to detect high-risk areas for occurrence and late diagnosis. A total of 40,060 new leprosy cases was reported in the period (mean = 2861 cases/year), 3296 (8.2%) in <15-year-olds, and 1921 (4.8%) with G2D. The new case detection rate was 20.41 cases/100,000 inhabitants (95% CI: 19.68⁻21.17). A higher risk was identified in older age groups (RR = 8.45, 95% CI: 7.08⁻10.09) and in residents living in the state capital (RR = 5.30, 95% CI: 4.13⁻6.79), in medium-sized cities (RR = 2.80; 95% CI: 2.50⁻3.13), and in the west (RR = 6.56, 95% CI: 5.13⁻8.39) and far south regions of the state (RR = 6.56, 95% CI: 5.13⁻8.39). A higher risk of G2D was associated with male gender (RR = 2.43, 95% CI: 2.20⁻2.67), older age (RR = 44.08, 95% CI: 33.21⁻58.51), Afro-Brazilian ethnicity (RR = 1.59; 95% CI: 1.37⁻1.85), living in medium-sized cities (RR = 2.60; 95% CI: 2.27⁻2.96) and residency in the north (RR = 5.02; 95% CI: 3.74⁻6.73) and far south (RR = 7.46; 95% CI: 5.58⁻9.98) regions. Heterogeneous space⁻time patterns of leprosy distribution were identified, indicating high endemicity, recent transmission, and late diagnosis. This heterogeneous distribution of the disease was observed throughout the study period. Leprosy remains a relevant public health problem in Bahia state. The disease has a focal distribution. We reinforce the importance of integrating surveillance, prevention and control actions in regions of higher risk of leprosy detection and late diagnosis, and in the most vulnerable populations.

Keywords: Brazil; epidemiology; leprosy; prevention and control; spatial analysis.

Figure 1

Study area: (A) location of the Bahia state; (B) Bahia state with its nine regions and 417 municipalities.

Figure 2

Spatiotemporal distribution of the overall new case detection rate of leprosy by municipality, Bahia state, 2001–2014: (A) crude detection rates (per 100,000 inhabitants); (B) Bayesian-smoothed detection rate (per 100,000 inhabitants); (C) hot-spot analysis (Getis-Ord Gi*) and (D) LISA cluster analysis (Moran Map).

Figure 3

Spatiotemporal distribution of the overall new case detection rate of leprosy in <15 year-olds by municipality, Bahia state, 2001–2014: (A) crude detection rates of new cases of leprosy (per 100,000 inhabitants); (B) Bayesian-smoothed detection rate (per 100,000 inhabitants); (C) hot-spot analysis (Getis-Ord Gi*) and (D) LISA cluster analysis (Moran Map).

Figure 4

Spatiotemporal distribution of G2D per million people by municipality, Bahia state, 2001–2014: (A) crude detection rate of new cases of leprosy (per 1,000,000 inhabitants); (B) Bayesian-smoothed detection rate (per 1,000,000 inhabitants); (C) hot-spot analysis (Getis-Ord Gi*) and (D) LISA cluster analysis (Moran Map).