BackgroundAlthough the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D) is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method.MethodsData were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk—RR) of leprosy. Maps considering these risks and their confidence intervals were constructed.ResultsA total of 434 cases were identified, including 188 (43.31%) borderline leprosy and 101 (23.28%) lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75%) presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000) contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721–4.267). Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133–52.984) and 15.24 (95%CI = 10.114–22.919).ConclusionThese findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting.

BackgroundBrazil is the only country in Latin America that has adopted a national health system. This causes differences in access to health among Latin American countries and induces noticeable migration to Brazilian regions to seek healthcare. This phenomenon has led to difficulties in the control and elimination of diseases related to poverty, such as leprosy. The aim of this study was to evaluate social determinants and their relationship with the risk of leprosy, as well as to examine the temporal trend of its occurrence in a Brazilian municipality located on the tri-border area between Brazil, Paraguay and Argentina.MethodsThis ecological study investigated newly-diagnosed cases of leprosy between 2003 and 2015. Exploratory analysis of the data was performed through descriptive statistics. For spatial analysis, geocoding of the data was performed using spatial scan statistic techniques to obtain the Relative Risk (RR) for each census tract, with their respective 95% confidence intervals calculated. The Bivariate Moran I test, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to analyze the spatial relationships of social determinants and leprosy risk. The temporal trend of the annual coefficient of new cases was obtained through the Prais-Winsten regression. A standard error of 5% was considered statistically significant (p < 0.05).ResultsOf the 840 new cases identified in the study, there was a predominance of females (n = 427, 50.8%), of white race/color (n = 685, 81.6%), age range 15 to 59 years (n = 624, 74.3%), and incomplete elementary education (n = 504, 60.0%). The results obtained from multivariate analysis revealed that the proportion of households with monthly nominal household income per capita greater than 1 minimum wage (β = 0.025, p = 0.036) and people of brown race (β = -0.101, p = 0.024) were statistically-significantly associated with risk of illness due to leprosy. These results also confirmed that social determinants and risk of leprosy were significantly spatially non-stationary. Regarding the temporal trend, a decrease of 4% (95% CI [-0.053, -0.033], p = 0.000) per year was observed in the rate of detection of new cases of leprosy.ConclusionThe social determinants income and race/color were associated with the risk of leprosy. The study’s highlighting of these social determinants can contribute to the development of public policies directed toward the elimination of leprosy in the border region.

OBJECTIVE: to analyze the temporal trend, identify the factors related and elaborate a predictive model for unfavorable treatment outcomes for multidrug-resistant tuberculosis (MDR-TB). METHODS: Retrospective cohort study with all cases diagnosed with MDR-TB between the years 2006 and 2015 in the state of São Paulo. The data were collected from the state system of TB cases notifications (TB-WEB). The temporal trend analyzes of treatment outcomes was performed through the Prais-Winsten analysis. In order to verify the factors related to the unfavorable outcomes, abandonment, death with basic cause TB and treatment failure, the binary logistic regression was used. Pictorial representations of the factors related to treatment outcome and their prognostic capacity through the nomogram were elaborated. RESULTS: Both abandonment and death have a constant temporal tendency, whereas the failure showed it as decreasing. Regarding the risk factors for such outcomes, using illicit drugs doubled the odds for abandonment and death. Besides that, being diagnosed in emergency units or during hospitalizations was a risk factor for death. On the contrary, having previous multidrug-resistant treatments reduced the odds for the analyzed outcomes by 33%. The nomogram presented a predictive model with 65% accuracy for dropouts, 70% for deaths and 80% for failure. CONCLUSIONS: The modification of the current model of care is an essential factor for the prevention of unfavorable outcomes. Through predictive models, as presented in this study, it is possible to develop patient-centered actions, considering their risk factors and increasing the chances for cure.