Spatial distribution of leprosy in areas of risk in Vitória, State of Espírito Santo, Brazil, 2005 to 2009.

INTRODUCTION: Leprosy remains a relevant public health issue in Brazil. The objective of this study was to analyze the spatial distribution of new cases of leprosy and to detect areas with higher risks of disease in the City of Vitória. METHODS: The study was ecologically based on the spatial distribution of leprosy in the City of Vitória, State of Espírito Santo between 2005 and 2009. The data sources used came from the available records of the State Health Secretary of Espírito Santo. A global and local empirical Bayesian method was used in the spatial analysis to produce a leprosy risk estimation, and the fluctuation effect was smoothed from the detection coefficients. RESULTS: The study used thematic maps to illustrate that leprosy is distributed heterogeneously between the neighborhoods and that it is possible to identify areas with high risk of disease. The Pearson correlation coefficient of 0.926 (p = 0.001) for the Local Method indicated highly correlated coefficients. The Moran index was calculated to evaluate correlations between the incidences of adjoining districts. CONCLUSIONS: We identified the spatial contexts in which there were the highest incidence rates of leprosy in Vitória during the studied period. The results contribute to the knowledge of the spatial distribution of leprosy in the City of Vitória, which can help establish more cost-effective control strategies because they indicate specific regions and priority planning activities that can interfere with the transmission chain.

Spatial distribution of leprosy in areas of risk in Vitoria, State of Espirito Santo, Brazil, 2005 to 2009

Introduction Leprosy remains a relevant public health issue in Brazil. The objective of this study was to analyze the spatial distribution of new cases of leprosy and to detect areas with higher risks of disease in the City of Vitória. Methods The study was ecologically based on the spatial distribution of leprosy in the City of Vitória, State of Espírito Santo between 2005 and 2009. The data sources used came from the available records of the State Health Secretary of Espírito Santo. A global and local empirical Bayesian method was used in the spatial analysis to produce a leprosy risk estimation, and the fluctuation effect was smoothed from the detection coefficients. Results The study used thematic maps to illustrate that leprosy is distributed heterogeneously between the neighborhoods and that it is possible to identify areas with high risk of disease. The Pearson correlation coefficient of 0.926 (p = 0.001) for the Local Method indicated highly correlated coefficients. The Moran index was calculated to evaluate correlations between the incidences of adjoining districts. Conclusions We identified the spatial contexts in which there were the highest incidence rates of leprosy in Vitória during the studied period. The results contribute to the knowledge of the spatial distribution of leprosy in the City of Vitória, which can help establish more cost-effective control strategies because they indicate specific regions and priority planning activities that can interfere with the transmission chain. .

Correlation between the spatial distribution of leprosy and socioeconomic indicators in the city of Vitória, State of ES, Brazil.

INTRODUCTION: Leprosy is a disease that is directly linked to poverty. The number of cases in Vit6ria, the capital city of Espírito Santo, has been decreasing in recent years, but the disease remains highly endemic. This research aimed to identify relationships between the epidemiological status of leprosy and socioeconomic indicators during the period from 2005 to 2009. METHODS: An ecological study was performed based on the spatial distribution of leprosy in Vit6ria, Espírito Santo, between 2005 and 2009. The source data used were records available at the Secretary of State for Health of the Espírito Santo. We used the Urban Quality Index (IQU) as the leprosy-associated socioeconomic variable. The data were analysed with covariate and spatial effects by the WinBugs programme (Version 1.4) and R (Version 2.12). RESULTS: The spatial distribution of leprosy in the district is not uniform. By studying the geographic distribution of leprosy cases, and the risks estimated by the complete Bayesian model, it was possible to gain further insight into the distribution of leprosy cases. It was noted that neighbourhoods with a low IQU have a higher leprosy case detection rate than neighbourhoods with a higher IQU. This result reinforced the theory that a low IQU is associated with the emergence of leprosy. CONCLUSION: The model methodology adopted enabled the verification of the effect of the influence of covariates related to the social determinants of health as well as the spatial structure, in contrast to the gross rate method that does not aggregate this information. The results obtained suggest that leprosy control may be promoted by improving the socioeconomic indicators of neighbourhoods, and highlights the need for implementation of health policies aimed at people who live in areas where they are at greatest risk of getting sick.

Spatial analysis of new cases of leprosy in the State of Espírito Santo, Brazil, between 2004 and 2009.

INTRODUCTION: Leprosy in Brazil is a public health issue, and there are many regions in the State of Espírito Santo with high endemic incidence levels of leprosy, characterizing this state as a priority for leprosy programs. The aim of this study was to determine the spatial distribution of coefficients of new cases of leprosy in the State of Espírito Santo, Brazil. METHODS: We conducted a descriptive and ecologic study based on the spatial distribution of leprosy in the State of Espírito Santo between 2004 and 2009. Data were gathered from the available records of the Espírito Santo State Health Secretary. The global and local Bayesian empirical methods were used to produce an estimate of leprosy risk, smoothing the fluctuation effects of the detection coefficients. RESULTS: The study resulted in a coefficient adjustment of new cases in 10 towns that changed their classification, among which, 2 went from low to medium, 4 from medium to high, 3 from high to very high, and 1 from very high to hyper-endemic. An average variation of 1.02, fluctuating between 0 and 12.39 cases/100,000 inhabitants, was found in a comparative calculation between the Local Ebest value and the average coefficient of new leprosy cases in the State of Espírito Santo. CONCLUSIONS: The spatial analysis of leprosy favors the establishment of control strategies with a better cost-benefit relationship since it reveals specific and priority regions, thereby enabling the development of actions that can interfere in the transmission chain.

Spatial analysis of new cases of leprosy in the State of Espírito Santo, Brazil, between 2004 and 2009 / Análise espacial dos casos novos de hanseníase no Estado do Espírito Santo, Brazil, entre 2004 e 2009

INTRODUCTION: Leprosy in Brazil is a public health issue, and there are many regions in the State of Espírito Santo with high endemic incidence levels of leprosy, characterizing this state as a priority for leprosy programs. The aim of this study was to determine the spatial distribution of coefficients of new cases of leprosy in the State of Espírito Santo, Brazil. METHODS: We conducted a descriptive and ecologic study based on the spatial distribution of leprosy in the State of Espírito Santo between 2004 and 2009. Data were gathered from the available records of the Espírito Santo State Health Secretary. The global and local Bayesian empirical methods were used to produce an estimate of leprosy risk, smoothing the fluctuation effects of the detection coefficients. RESULTS: The study resulted in a coefficient adjustment of new cases in 10 towns that changed their classification, among which, 2 went from low to medium, 4 from medium to high, 3 from high to very high, and 1 from very high to hyper-endemic. An average variation of 1.02, fluctuating between 0 and 12.39 cases/100,000 inhabitants, was found in a comparative calculation between the Local Ebest value and the average coefficient of new leprosy cases in the State of Espírito Santo. CONCLUSIONS: The spatial analysis of leprosy favors the establishment of control strategies with a better cost-benefit relationship since it reveals specific and priority regions, thereby enabling the development of actions that can interfere in the transmission chain.

INTRODUÇÃO: A hanseníase no Brasil ainda é um problema de saúde publica e, no Estado do Espírito Santo, Brasil, há várias regiões com elevados níveis endêmicos, fato que o coloca entre os prioritários para o programa de controle da hanseníase. O objetivo deste estudo é determinar a distribuição espacial dos coeficientes de casos novos de hanseníase no Estado do Espírito Santo. MÉTODOS: Estudo descritivo, ecológico baseado na distribuição espacial da hanseníase no Estado do Espírito Santo, entre 2004 e 2009. A fonte de dados utilizada foram os registros disponíveis na Secretaria de Estado da Saúde do Espírito Santo. Na análise espacial, foi aplicado o método bayesiano empírico global e local para produzir uma estimativa do risco da hanseníase, suavizando o efeito da flutuação dos coeficientes de detecção. RESULTADOS: O estudo resultou em ajuste de coeficiente de casos novos em 10 municípios que mudaram de classificação, sendo dois de baixo para médio, quatro de médio para alto, três de alto para muito alto e um município mudou da categoria muito alto para hiperendêmico. Através de um calculo comparativo entre o Ebest Local e o coeficiente médio de detecção de casos novos de hanseníase do Estado do Espírito Santo houve uma variação média de 1,02, flutuando entre zero a 12,39 por 100.000 habitantes. CONCLUSÕES: A análise espacial da hanseníase favorece o estabelecimento de estratégias de controle com uma melhor relação custo-benefício, pois indica regiões específicas e prioritárias, planejando ações a fim de interferir na cadeia de transmissão.