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巴西东北部高度流行地区报告新病例和当地麻风病局部风险的空间分析。

Spatial analysis of reported new cases and local risk of leprosy in hyper-endemic situation in Northeastern Brazil.

机构信息

Department of Collective Health, Aggeu Magalhães Institute, Oswaldo Cruz Foundation, Recife, Brazil.

Department of Epidemiological Surveillance, First Health District of the State Health Department of Pernambuco, Recife, Brazil.

出版信息

Trop Med Int Health. 2018 Jul;23(7):748-757. doi: 10.1111/tmi.13067. Epub 2018 May 23.

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.

摘要

目的

分析巴西东北部麻风病发病率的空间分布,并确定高流行地区的发病风险。

方法

采用以市为分析单位的生态研究。麻风病新发病例数据来自卫生危害警报系统(SINAN)。本研究聚焦于伯南布哥州,涵盖了 2005 年至 2014 年的数据。监测指标按每 10 万人计算。采用局部经验贝叶斯方法最小化率方差,并使用空间自相关图进行空间模式分析(箱线图和 Moran 图)。

结果

研究期间共登记了 28895 例新发病例。平均发病率为 21.88/10 万;全局 Moran's I 指数为 0.36(P<0.01),表明存在空间依赖性;Moran 图确定了 20 个需要重点关注的高优先级市。15 岁以下人群的平均发病率为 8.78/10 万;全局 Moran's I 指数显示存在正空间自相关(0.43;P<0.01),Moran 图显示了 15 个高流行市的主要集群。诊断时二级身体残疾的平均发生率为 1.12/10 万;全局 Moran 指数呈现正空间关联(0.17;P<0.01);Moran 图在三个中地区定位了市的集群(高高)。

结论

应用不同的空间分析方法可以定位仅通过流行病学指标无法识别的区域。

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