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OBJECTIVES: To analyse and map the leprosy risk areas in the state of Alagoas, an endemic region in the Northeastern Brazil, between 2001 and 2019. METHODS: Ecological and time series study, using spatial analysis techniques. First, we analyse the epidemiological aspects of leprosy cases, using the data available in the Notifiable Diseases Information System; then, we used the segmented log‐linear regression model to assess time trends. Spatial distribution was analysed by the Local Empirical Bayesian Estimator and by calculating the Global and Local Moran Index. Finally, spatiotemporal clusters were identified through scanning statistics, using the Kulldorf method of retrospective analysis. RESULTS: We observed that Alagoas showed an average new case detection rate of 14.43/100,000 inhabitants between 2001 and 2019, being classified as highly endemic. The area of highest risk was the 9th health region (state hinterland), with increasing time trend (Annual Percentage Change/APC = 7.2; p‐value < 0.05). Several clusters of high risk of leprosy transmission were verified in Alagoas, including the state capital and hinterland municipalities. CONCLUSIONS: Our data indicate that active M. leprae transmission persists in Alagoas; that diagnosis is delayed and that there are high‐risk areas, especially in inland municipalities. [ABSTRACT FROM AUTHOR]

Objectives: to analyze the epidemiological profile and the spatial-temporal dynamics on maternal mortality in Alagoas and its relationship with social vulnerability and income inequality. Methods: a mixed ecological study involving maternal deaths who resided in Alagoas from 1996 to 2016. Sociodemographic variables (age, race/color, education, marital status), clinical (type of obstetric cause, death by category and ICD group) were analyzed, besides the indicators (Maternal Mortality Ratio- MMR, Social Vulnerability Index and Gini Index). For the temporal analysis, we used the inflection point regression model and for the spatial analysis, the local empirical Bayesian model, Moran Global and Local statistics, and the bivariate local spatial autocorrelation analysis. Results: a total of 586 deaths (47.63/100 thousand live births) were registered, with a trend of MMR growth (APC 2.8%), with a heterogeneous distribution between health regions and cities. The profile was characterized by the predominance of young, black / mixed skin color women with low schooling. Eight cities were considered priority. There was spatial correlation with the Social Vulnerability Index and income inequality. Conclusions: identifying priority areas may contribute to planning and targeting interventions. [ABSTRACT FROM AUTHOR]