Department of Community Health, School of Medicine, Federal University of Ceará, Fortaleza, Brazil.
Trop Med Int Health. 2012 Apr;17(4):518-25. doi: 10.1111/j.1365-3156.2011.02945.x. Epub 2012 Jan 16.
The Brazilian National Hansen's Disease Control Program recently identified clusters with high disease transmission. Herein, we present different spatial analytical approaches to define highly vulnerable areas in one of these clusters.
The study area included 373 municipalities in the four Brazilian states Maranhão, Pará, Tocantins and Piauí. Spatial analysis was based on municipalities as the observation unit, considering the following disease indicators: (i) rate of new cases/100,000 population, (ii) rate of cases <15 years/100,000 population, (iii) new cases with grade-2 disability/100,000 population and (iv) proportion of new cases with grade-2 disabilities. We performed descriptive spatial analysis, local empirical Bayesian analysis and spatial scan statistic.
A total of 254 (68.0%) municipalities were classified as hyperendemic (mean annual detection rates >40 cases/100,000 inhabitants). There was a concentration of municipalities with higher detection rates in Pará and in the center of Maranhão. Spatial scan statistic identified 23 likely clusters of new leprosy case detection rates, most of them localized in these two states. These clusters included only 32% of the total population, but 55.4% of new leprosy cases. We also identified 16 significant clusters for the detection rate <15 years and 11 likely clusters of new cases with grade-2. Several clusters of new cases with grade-2/population overlap with those of new cases detection and detection of children <15 years of age. The proportion of new cases with grade-2 did not reveal any significant clusters.
Several municipality clusters for high leprosy transmission and late diagnosis were identified in an endemic area using different statistical approaches. Spatial scan statistic is adequate to validate and confirm high-risk leprosy areas for transmission and late diagnosis, identified using descriptive spatial analysis and using local empirical Bayesian method. National and State leprosy control programs urgently need to intensify control actions in these highly vulnerable municipalities.
巴西国家麻风病控制规划最近发现了一些具有高疾病传播率的聚集区。在此,我们介绍了不同的空间分析方法,以确定其中一个聚集区的高脆弱性地区。
研究区域包括巴西马拉尼昂州、帕拉州、托坎廷斯州和皮奥伊州的 373 个市。空间分析以市为观察单位,考虑以下疾病指标:(i)每 10 万人中新发病例率,(ii)每 10 万人中<15 岁病例率,(iii)每 10 万人中残疾 2 级新发病例率,(iv)残疾 2 级新发病例比例。我们进行了描述性空间分析、局部经验贝叶斯分析和空间扫描统计分析。
共有 254 个(68.0%)市被归类为高流行区(年平均检出率>40 例/10 万人)。帕拉州和马拉尼昂州中部的市检出率较高。空间扫描统计发现了 23 个可能的新麻风病病例检出率聚集区,其中大多数位于这两个州。这些聚集区仅占总人口的 32%,但占新麻风病病例的 55.4%。我们还发现了 16 个新病例<15 岁检出率的显著聚集区和 11 个新病例 2 级残疾检出率的可能聚集区。新病例 2 级残疾/人口的几个聚集区与新病例检出和 15 岁以下儿童检出的聚集区重叠。新病例 2 级残疾比例没有显示出任何显著的聚集区。
使用不同的统计方法,在一个流行地区发现了一些具有高麻风病传播和晚期诊断的市集群。空间扫描统计分析适用于验证和确认使用描述性空间分析和局部经验贝叶斯方法确定的高风险麻风病传播和晚期诊断区域。国家和州麻风病控制规划急需加强对这些高脆弱性市的控制措施。