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运用时空扫描统计法对日本血吸虫病感染风险进行精细尺度的时空聚类分析。

Fine scale Spatial-temporal cluster analysis for the infection risk of Schistosomiasis japonica using space-time scan statistics.

作者信息

Gao Feng-hua, Abe Eniola Michael, Li Shi-zhu, Zhang Li-juan, He Jia-Chang, Zhang Shi-qing, Wang Tian-ping, Zhou Xiao-nong, Gao Jing

机构信息

Anhui Provincial Institute of Schistosomiasis Control, Hefei, 230061, China.

Department of Zoology, Federal University Lafia, P.M. B 146, Lafia, Nasarawa State, Nigeria.

出版信息

Parasit Vectors. 2014 Dec 10;7:578. doi: 10.1186/s13071-014-0578-3.

Abstract

BACKGROUND

Marching towards the elimination of schistosomiasis in China, both the incidence and prevalence have witnessed profound decline over the past decades, with the strategy shifting from morbidity control to transmission control. The current challenge is to find out hotspots of transmission risk for precise targeted control in low-prevalence areas. This study assessed the risk at the village level, using the spatial and temporal characteristics of Schistosomiasis japonica in Anhui province from 2006 to 2012.

METHOD

The comprehensive database was generated from annual surveillance data at village level in Anhui province between 2006 and 2012, comprising schistosomiasis prevalence among humans and cattle, occurrence rate of infected environments and incidence rate of acute schistosomiasis. The database parameters were matched with geographic data of the study area and fine scale spatial-temporal cluster analysis based on retrospective space-time scan statistics was used to assess the clustering pattern of schistosomiasis. The analysis was conducted by using SaTScan 9.1.1 and ArcGIS 10.0. A spatial statistical modelling was carried out to determine the spatial dependency of prevalence of human infection by using Geoda 1.4.3.

RESULT

A pronounced decline was found in the prevalence of human infection, cattle infection, occurrence rate of environment with infected vector snails and incidence rate of acute schistosomiasis from 2006 to 2012 by 48.6%, 71.5%, 91.9% and 96.4%, respectively. Meanwhile, all 4 indicators showed a statistically significant clustering pattern both in time and space, with a total of 16, 6, 8 and 4 corresponding clustering foci found respectively. However, the number of clustering foci declined with time, and none was found after year 2010. All clustering foci were mainly distributed along the Yangtze River and its connecting branches. The result shows that there is a direct spatial relationship between prevalence of human infection and the other indicators.

CONCLUSION

A decreasing trend in space-time clustering of schistosomiasis endemic status was observed between 2006 and 2012 in Anhui province. Nevertheless, giving the complexity in schistosomiasis control, areas within the upper-stream of Yangtze River in Anhui section and its connecting branches should be targeted for effective implementation of control strategies in the future.

摘要

背景

在中国朝着消除血吸虫病迈进的过程中,发病率和患病率在过去几十年中都有显著下降,策略也从发病率控制转向传播控制。当前的挑战是找出低流行地区传播风险的热点区域,以便进行精准靶向控制。本研究利用2006年至2012年安徽省日本血吸虫病的时空特征,评估了村级层面的风险。

方法

综合数据库来自2006年至2012年安徽省村级年度监测数据,包括人群和牛的血吸虫病患病率、感染环境发生率以及急性血吸虫病发病率。将数据库参数与研究区域的地理数据进行匹配,并基于回顾性时空扫描统计进行精细尺度的时空聚类分析,以评估血吸虫病的聚类模式。分析使用SaTScan 9.1.1和ArcGIS 10.0进行。利用Geoda 1.4.3进行空间统计建模,以确定人群感染患病率的空间依赖性。

结果

2006年至2012年期间,人群感染率、牛感染率、感染钉螺环境发生率和急性血吸虫病发病率分别显著下降了48.6%、71.5%、91.9%和96.4%。同时,所有4项指标在时间和空间上均呈现出具有统计学意义的聚类模式,分别共发现16个、6个、8个和4个相应的聚类焦点。然而,聚类焦点的数量随时间减少,2010年后未再发现。所有聚类焦点主要分布在长江及其支流沿线。结果表明,人群感染患病率与其他指标之间存在直接的空间关系。

结论

2006年至2012年期间,安徽省血吸虫病流行状况的时空聚类呈下降趋势。尽管如此,鉴于血吸虫病控制的复杂性,未来应将安徽省长江段上游及其支流区域作为有效实施控制策略的目标区域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f409/4273478/ec0844c2bedf/13071_2014_578_Fig1_HTML.jpg

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