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首页> 外文期刊>Tropical Medicine and International Health: TM and IH >Spatial analysis of reported new cases and local risk of leprosy in hyper‐endemic situation in Northeastern Brazil
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Spatial analysis of reported new cases and local risk of leprosy in hyper‐endemic situation in Northeastern Brazil

机译:巴西东北地区海洋流行情况下新病例及麻风病风险的空间分析

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Abstract Objective To analyse the spatial distribution of the incidence of leprosy and identify areas at risk for occurrences of hyper‐endemic disease in Northeastern Brazil. Methods Ecological study using municipalities as the analysis unit. Data on new cases of leprosy came from the Health Hazard Notification System ( SINAN ). This study focused on Pernambuco and covered the years 2005 to 2014. Indicators for monitoring were calculated per 100 000 inhabitants. The local empirical Bayes method was used to minimise rate variance, and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps). Results A total of 28 895 new cases were registered in the study period. The average incidence was 21.88/100 000; the global Moran's I index was 0.36 ( P 0.01), thus indicating the existence of spatial dependence; and the Moran map identified 20 municipalities with high priority for attention. The average incidence rate among individuals under 15 years of age was 8.78/100 000; the global Moran's I index showed the presence of positive spatial autocorrelation (0.43; P 0.01), and the Moran map showed a main cluster of 15 hyper‐endemic municipalities. The average rate of grade 2 physical disability at the time of diagnosis was 1.12/100 000; the global Moran index presented a positive spatial association (0.17; P 0.01); and the Moran map located clusters of municipalities (high‐high) in three mesoregions. Conclusion Application of different spatial analysis methods made it possible to locate areas that would not have been identified by epidemiological indicators alone.
机译:摘要目的分析麻风病发生率的空间分布,并鉴定巴西东北地区高脂疾病患病风险。方法使用城市作为分析单位的生态学研究。关于Leprosy新病例的数据来自健康危险通知系统(SINAN)。本研究专注于Pernambuco,并涵盖了2005年至2014年。监测指标每100 000名居民计算。本地经验贝叶斯方法用于最小化速率方差,并且空间自相关地图用于空间模式分析(框图和莫兰地图)。结果共有28895例新案件在研究期间注册。平均发病率为21.88 / 100 000;全球莫兰的I指数为0.36(P <0.01),从而表明存在空间依赖性;莫兰地图确定了20个关注优先事项的20个市政当局。 15岁以下的个体的平均发病率为8.78 / 100 000;全球莫兰的I指数显示出积极空间自相关的存在(0.43; P& 0.01),莫兰地图显示了15个超流域市的主要集群。诊断时2级身体残疾的平均率为1.12 / 100 000;全球莫兰指数呈现出正空间关联(0.17; P& 0.01);和莫兰地图定位在三种中间的城市(高高)的集群。结论不同空间分析方法的应用使得可以单独通过流行病学指标鉴定的区域。

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