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Vigilancia da hanseníase em Olinda, Brasil, utilizando técnicas de análise espacial

机译:使用空间分析技术在巴西奥林达进行麻风监测

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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.
机译:在巴西伯南布哥州,麻风病主要是一种城市疾病,其地理分布不均至少部分与城市空间的占用和转变有关。空间分析因此可能成为建立麻风流行病学监测系统的重要工具。通过整合人口普查和SINAN这两个数据库,并通过使用数字地图和地理处理技术,在奥林达市定义了同质的微区域。根据社会剥夺指数(SDI)对人口普查区进行分类,并且微区域均一性基于该指标的相似值。聚类分析(K均值)用于定义各层之间的临界值。仅使用收入变量重复相同的过程。当对1991-1996年期间的SDI平均值与麻风病平均检出率进行关联检验时,在乘法模型中r2的取值为66.1%,当使用收入变量时,该值升至84.3%。为了定义不同的干预策略,将人口普查区分为三个风险级别:高,中和低。该方法可以识别(在每个卫生区中)麻风风险不同的人群和/或地区,因此可以定义控制措施。

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