OBJETIVO: Analisar a distribuição espacial da hanseníase, identificar áreas de possível sub-registro de casos ou de provável alta transmissão (risco) e verificar a associação dessa distribuição à existência de casos de formas multibacilares. MÉTODOS: O estudo foi realizado em Recife, PE, de acordo com 94 bairros analisados. A fonte de coleta de dados foi o Sistema de Informações sobre Agravos de Notificação do Ministério da Saúde. Foi adotada uma abordagem ecológica com utilização do método bayesiano empírico para suavização local de taxas, a partir de informações de bairros vizinhos por adjacência. RESULTADOS: A ocorrência média anual foi de 17,3% de casos novos em menores de 15 anos (28,3% de formas multibacilares), indicando um processo de intensa transmissão da doença. A análise da distribuição espacial de hanseníase apontou três áreas onde se concentram bairros com taxas de detecção elevadas e que possuem baixa condição de vida. CONCLUSÕES: O emprego do modelo bayesiano, baseado em informações de unidades espaciais vizinhas, permitiu estimar novamente indicadores epidemiológicos. Foi possível identificar áreas prioritárias para o programa de controle de hanseníase no município, tanto pelo elevado número de ocorrências correlacionado à presença de formas multibacilares de doença em menores de 15 anos quanto pela existência de subnotificação.
In this article we discuss the methodological issues associated with the creation of a surveillance system for endemic diseases in urban areas based on analysis of populations at risk and on spatially referenced epidemiological indicators. We comment on the system's basic requirements, selection criteria for socioeconomic variables, and methodological steps to combine these variables so as to construct a census-based deprivation index. We also present the ways we solved some operational problems related to generation of digitized census tracts maps and linkage of morbidity data from different sources. This approach, spatial organization into account in surveillance of endemic diseases, exemplified here by tuberculosis and leprosy, allows for the interaction of several official data sets from census and health services in order to geographically discriminate inner-city risk strata. Criteria for constructing these risk strata were considered a useful tool for health planning and management activities for the control of endemic diseases in cities.
In the State of Pernambuco, Brazil, leprosy has been mainly an urban disease, with an uneven geographical distribution related at least partially to the way urban space has been occupied and transformed. Spatial analysis may thus become an important tool to establish an epidemiological surveillance system for leprosy. Homogeneous micro-areas were defined in the city of Olinda through the integration of two databases, the Population Census and SINAN, and through the use of digital maps and geoprocessing techniques. Census tracts were classified according to a social deprivation index (SDI), and micro-area homogeneity was based on similar values for this indicator. Cluster analysis (K-means) was used to define cut-offs between strata. The same procedure was repeated using the income variable only. When the association was tested between the mean SDI value and the mean leprosy detection rate for the period 1991-1996, the value obtained for r2 was 66.1% in the multiplicative model, increasing to 84.3% when the income variable was used. To define different intervention strategies, census tracts were regrouped in three levels of risk: high, moderate, and low. The methodology enabled the identification (within each health district) of groups and/or areas with different risk of leprosy, hence allowing for the definition of control measures.
Hansen disease or leprosy is a major endemic disease in Brazil. Well-designed strategies, including decentralization of basic care, are needed to reduce its prevalence. The article begins by describing the structure and supply of services for treating leprosy cases in the country, after which it analyzes the trends in epidemiological and operational indicators, comparing the periods before and after decentralization of services to the municipal (local) level. Finally, spatial analysis allowed identifying the territorial distribution of this endemic and analyzing the pattern of geographic areas according to care provided by health facilities and its evolution. Based on the location of the geographic centers in the census tracts by place of residence, and using spatial smoothing technique based on Kernel estimation, the study constructed domain areas of care for each health facility or unit. Following municipalization of care, there was an increase in the detection and treatment by the municipalities themselves, reducing patient evasion to neighboring counties and causing changes in demand trends, with an increase in use of services by the clientele and important alterations in the epidemiological and operational indicators.
This study suggests that the violence clusters are not the result of the socioeconomic conditions per se, but rather the consequence of the interaction between poor economic conditions and drug trafficking.
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