[Spatial modeling of leprosy in the state of Bahia, Brazil, (2001-2015) and social determinants of health]. / Modelagem espacial da hanseníase no estado da Bahia, Brasil, (2001-2015) e determinantes sociais da saúde.

This work analyzes the spatial distribution of leprosy in Bahia and associated social determinants. It is an ecological study, with leprosy data from 2001-2015. Three epidemiological indicators were selected: coefficient of detection in the general population and in children under 15 and the rate of new cases with grade II physical disability. These indicators were flattened by the Local Empirical Bayesian Model and Global and Local Moran statistics were applied. The independent variables were selected from the IBGE-2010 Census. Multivariate regressions were employed, followed by spatial regression. Leprosy exhibited a heterogeneous distribution in the state, with concentration in the north-west axis and the south region. For the general detection coefficient, five variables composed the final model: demographic density, urban population proportion, per capita income, proportion of extremely poor and households with over three people per dormitory. The illiteracy proportion made up the final model for the grade II rate of physical disability. No determinants of the occurrence of the disease were identified in children under 15. The modeling used contributed to demonstrate the spatial heterogeneity and social determinants of the disease in Bahia, revealing the complexity of the problem.

O trabalho analisa a distribuição espacial da hanseníase na Bahia e os determinantes sociais relacionados. Estudo ecológico com dados de hanseníase do período 2001-2015. Três indicadores epidemiológicos foram selecionados: coeficiente de detecção na população geral e em menores de 15 anos e a taxa de casos novos com grau II de incapacidade. Os indicadores foram suavizados pelo Modelo Bayesiano Empírico Local e aplicou-se estatística de Moran Global e Local. As variáveis independentes foram selecionadas a partir do Censo IBGE-2010. Regressões multivariadas foram empregadas, seguidas de regressão espacial. Observou-se distribuição heterogênea no estado, com concentração no eixo norte-oeste e região sul. Para o coeficiente de detecção geral, cinco variáveis compuseram o modelo: densidade demográfica, proporção da população urbana, renda per capita, proporção de extremamente pobres e domicílios com mais de três pessoas por dormitório. A proporção de analfabetismo compôs o modelo final para a taxa de grau II de incapacidade física. Não foram identificados determinantes da ocorrência da doença em menores de 15 anos. A modelagem utilizada contribuiu para demonstrar a heterogeneidade espacial e os determinantes sociais da doença na Bahia, colocando em evidência a complexidade do problema.

Modelagem espacial da hanseníase no estado da Bahia, Brasil, (2001-2015) e determinantes sociais da saúde / Spatial modeling of leprosy in the state of Bahia, Brazil, (2001-2015) and social determinants of health

Resumo O trabalho analisa a distribuição espacial da hanseníase na Bahia e os determinantes sociais relacionados. Estudo ecológico com dados de hanseníase do período 2001-2015. Três indicadores epidemiológicos foram selecionados: coeficiente de detecção na população geral e em menores de 15 anos e a taxa de casos novos com grau II de incapacidade. Os indicadores foram suavizados pelo Modelo Bayesiano Empírico Local e aplicou-se estatística de Moran Global e Local. As variáveis independentes foram selecionadas a partir do Censo IBGE-2010. Regressões multivariadas foram empregadas, seguidas de regressão espacial. Observou-se distribuição heterogênea no estado, com concentração no eixo norte-oeste e região sul. Para o coeficiente de detecção geral, cinco variáveis compuseram o modelo: densidade demográfica, proporção da população urbana, renda per capita, proporção de extremamente pobres e domicílios com mais de três pessoas por dormitório. A proporção de analfabetismo compôs o modelo final para a taxa de grau II de incapacidade física. Não foram identificados determinantes da ocorrência da doença em menores de 15 anos. A modelagem utilizada contribuiu para demonstrar a heterogeneidade espacial e os determinantes sociais da doença na Bahia, colocando em evidência a complexidade do problema.

Abstract This work analyzes the spatial distribution of leprosy in Bahia and associated social determinants. It is an ecological study, with leprosy data from 2001-2015. Three epidemiological indicators were selected: coefficient of detection in the general population and in children under 15 and the rate of new cases with grade II physical disability. These indicators were flattened by the Local Empirical Bayesian Model and Global and Local Moran statistics were applied. The independent variables were selected from the IBGE-2010 Census. Multivariate regressions were employed, followed by spatial regression. Leprosy exhibited a heterogeneous distribution in the state, with concentration in the north-west axis and the south region. For the general detection coefficient, five variables composed the final model: demographic density, urban population proportion, per capita income, proportion of extremely poor and households with over three people per dormitory. The illiteracy proportion made up the final model for the grade II rate of physical disability. No determinants of the occurrence of the disease were identified in children under 15. The modeling used contributed to demonstrate the spatial heterogeneity and social determinants of the disease in Bahia, revealing the complexity of the problem.

Spatial modeling of leprosy in the state of Bahia and its social determinants: a study of health inequities.

BACKGROUND: Leprosy is a neglected disease caused by Mycobacterium leprae. Brazil has the second largest number of cases in the world. OBJECTIVES: To analyze the spatial distribution of leprosy in the state of BAHIA, Brazil, and the association between his occurrence and the synthetic indicators of municipal socioeconomic performance, social vulnerability and income inequality. METHODS: An ecological study with secondary data obtained from the National System of Notifiable Diseases. Dependent variables: coefficient of detection in the general population and in the population under 15 years old and the rate of grade II of physical disability. Independent variables: Synthetic indicators of socioeconomic performance, social vulnerability and income inequality. RESULTS: The highest coefficients of detection of new cases in the general population and in children under 15 years old are concentrated in the north-west axis and in the southern region of the state. On the other hand, the highest rates of degree II of physical incapacity are concentrated in the north, northeast and south regions. Only the Index of Social and Economic Performance(IPESE)-Economy and Finance composed the final regression model of the general detection coefficients and in children under 15 years old. The municipalities with the highest indexes had the highest detection coefficients, reflecting the capacity to diagnose new cases. STUDY LIMITATIONS: The use of synthetic indicators is a limitation of the study. CONCLUSIONS: Leprosy presents a heterogeneous spatial pattern in the state of BAHIA, and the IPESE-Economics and Finance indicator is the only one with explanatory potential of the disease.

Leprosy transmission in Bahia, 2001-2015: modeling based on Jointpoint regression and spatial scan statistics. / Transmissão da hanseníase na Bahia, 2001-2015: modelagem a partir de regressão por pontos de inflexão e estatística de varredura espacial.

OBJECTIVE: to describe the trend and the spatial distribution of leprosy in the state of Bahia, Brazil, 2001-2015. METHODS: this was a mixed ecological study of epidemiological indicators of leprosy; Jointpoint regression was used for the temporal analysis, while spatial scan statistics were used to identify clusters of the disease; the trend was classified as stationary, increasing or decreasing; we calculated the annual percent change (APC) and average annual percent change (AAPC). RESULTS: there was a reduction in prevalence (AAPC = -5.6; p<0,001), treatment dropout (AAPC = -13.7; p<0.001), and females with leprosy (AAPC = -0.6; p<0.001); the new grade II case coefficient (AAPC = 2.7; p<0.001) and the proportion of multibacillary cases (AAPC = 2,2; p<0.001) showed a growing trend; spatial distribution was heterogeneous and concentrated in three regions in particular (north, west and south of the state), with variation between the indicators. CONCLUSION: persisting leprosy transmission in the state, late diagnosis and high hidden prevalence is suggested.

Spatial modeling of leprosy in the state of Bahia and its social determinants: a study of health inequities

Abstract BACKGROUND: Leprosy is a neglected disease caused by Mycobacterium leprae. Brazil has the second largest number of cases in the world. OBJECTIVES: To analyze the spatial distribution of leprosy in the state of BAHIA, Brazil, and the association between his occurrence and the synthetic indicators of municipal socioeconomic performance, social vulnerability and income inequality. METHODS: An ecological study with secondary data obtained from the National System of Notifiable Diseases. Dependent variables: coefficient of detection in the general population and in the population under 15 years old and the rate of grade II of physical disability. Independent variables: Synthetic indicators of socioeconomic performance, social vulnerability and income inequality. RESULTS: The highest coefficients of detection of new cases in the general population and in children under 15 years old are concentrated in the north-west axis and in the southern region of the state. On the other hand, the highest rates of degree II of physical incapacity are concentrated in the north, northeast and south regions. Only the Index of Social and Economic Performance(IPESE)-Economy and Finance composed the final regression model of the general detection coefficients and in children under 15 years old. The municipalities with the highest indexes had the highest detection coefficients, reflecting the capacity to diagnose new cases. STUDY LIMITATIONS: The use of synthetic indicators is a limitation of the study. CONCLUSIONS: Leprosy presents a heterogeneous spatial pattern in the state of BAHIA, and the IPESE-Economics and Finance indicator is the only one with explanatory potential of the disease.

Transmissão da hanseníase na Bahia, 2001-2015: modelagem a partir de regressão por pontos de inflexão e estatística de varredura espacial / Transmisión de la lepra en Bahia, 2001-2015: modelado a partir de regresión por Joinpoint y estadística de barrido espacial / Leprosy transmission in Bahia, 2001-2015: modeling based on Jointpoint regression and spatial scan statistics

Objetivo: descrever a tendência e a distribuição espacial da hanseníase no estado da Bahia, Brasil, em 2001-2015. Métodos: estudo ecológico misto dos indicadores epidemiológicos da hanseníase; na análise temporal, utilizou-se a regressão Joinpoint, e a estatística de varredura espacial na identificação de clusters da doença; a tendência foi classificada como estacionária, crescente ou decrescente; calculou-se a variação percentual anual (APC: annual percent change) e a variação percentual anual média (AAPC: average annual percent change). Resultados: houve redução da prevalência (AAPC = -5,6; p<0,001), do abandono (AAPC = -13,7; p<0,001) e de mulheres doentes (AAPC = -0,6; p<0,001); o coeficiente de casos novos de grau II (AAPC = 2,7; p<0,001) e a proporção de casos multibacilares (AAPC = 2,2; p<0,001) apresentaram tendência crescente; revelou-se distribuição espacial heterogênea, concentrada em três regiões destacadas (norte, oeste e sul do estado), e variação entre indicadores. Conclusão: sugere-se persistência da transmissão da hanseníase no estado, diagnóstico tardio e elevada prevalência oculta.

Objetivo: describir la tendencia y distribución espacial de la lepra en el estado de Bahia, Brasil, en 2001-2015. Métodos: estudio ecológico mixto de los indicadores epidemiológicos de la lepra; se utilizó la regresión Joinpoint para el análisis temporal y la estadística espacial para la identificación de clusters de la enfermedad; la tendencia se clasificó en estacionaria, creciente o decreciente; se calculó el cambio porcentual anual (APC: annual percent change) y la variación porcentual anual promedio (AAPC: average annual percent change). Resultados: se ha reducido la prevalencia (AAPC = -5,6; p<0,001), el abandono (AAPC = -13,7; p<0,001) y las mujeres enfermas (AAPC = -0,6; p<0,001); la tasa de nuevos casos de grado II (AAPC = 2,7; p<0,001) y la proporción de casos multibacilares (AAPC = 2,2; p<0,001) presentaron una tendencia de crecimiento; la distribución espacial fue heterogénea, con concentración en tres regiones de destaque (norte, oeste y sur del estado) y variación entre indicadores. Conclusión: sugiere persistencia de la transmisión de la lepra en el estado, diagnóstico tardío y elevada prevalencia oculta.

Objective: to describe the trend and the spatial distribution of leprosy in the state of Bahia, Brazil, 2001-2015. Methods: this was a mixed ecological study of epidemiological indicators of leprosy; Jointpoint regression was used for the temporal analysis, while spatial scan statistics were used to identify clusters of the disease; the trend was classified as stationary, increasing or decreasing; we calculated the annual percent change (APC) and average annual percent change (AAPC). Results: there was a reduction in prevalence (AAPC = -5.6; p<0,001), treatment dropout (AAPC = -13.7; p<0.001), and females with leprosy (AAPC = -0.6; p<0.001); the new grade II case coefficient (AAPC = 2.7; p<0.001) and the proportion of multibacillary cases (AAPC = 2,2; p<0.001) showed a growing trend; spatial distribution was heterogeneous and concentrated in three regions in particular (north, west and south of the state), with variation between the indicators. Conclusion: persisting leprosy transmission in the state, late diagnosis and high hidden prevalence is suggested.