中国血吸虫病防治杂志 ›› 2012, Vol. 24 ›› Issue (1): 72-75.

• 短篇论著 • 上一篇    下一篇

基于行政村尺度的安乡县晚期血吸虫病空间分布特征研究

姚保栋1|周艺彪1*|王增亮1|田安平2|朱绍平2|胡本骄3|张志杰1|宋秀霞1|易平3|姜庆五1   

  1. 1复旦大学公共卫生学院流行病学教研室、 公共卫生安全教育部重点实验室 (上海 200032); 2 湖南省安乡县血吸虫病防治工作领导小组办公室;3 湖南省血吸虫病防治所
  • 出版日期:2012-02-16 发布日期:2012-02-15
  • 通讯作者: 周艺彪
  • 作者简介:姚保栋| 男| 硕士研究生。 研究方向: 感染性疾病流行病学
  • 基金资助:
    国家高技术研究发展技术 (863计划)(2006AA02Z402)

Study on spatial distribution of advanced schistosomiasis at village level in Anxiang County based on geographic information system

Yao Bao-dong1 |Zhou Yi-biao1* |Wang Zeng-liang1 |Tian An-ping2 |Zhu Shao-ping2 |Hu Ben-jiao3 |Zhang Zhi-jie1 |Song Xiu- xia1 | Yi Ping3 | Jiang Qing-wu1   

  1. 1 Department of Epidemiology|School of Public Health|Fudan University|Key Laboratory on Public Health Safety|Ministry of Ed? ucation|Shanghai 200032|China; 2 Anxiang Office of Leading Group for Schistosomiasis Control|China;3 Hunan Institute of Parasitic Diseases| China
  • Online:2012-02-16 Published:2012-02-15
  • Contact: Zhou Yi?biao

摘要:

目的 目的 探讨安乡县晚期血吸虫病 (晚血) 的空间分布模式及规律, 为晚血的有效防控提供科学依据。 方法 方法 建立安乡县基于行政村的空间数据库, 运用全局空间自相关 (Moran’ s I)、 局部空间自相关 (Local Moran’ s I,LISA)与空间扫描统计量法探索晚血空间分布特征。 结果 结果 全局空间自相关结果显示, 总体研究区域上晚血患病率不存在空间自相关 (Mo? ran’ s I = 0.06,P > 0.05); 局部空间自相关分析探测出9个村的LISA值差异有统计学意义 (P < 0.05), 其中H?H、 L?H、 H?L 3 种相关模式的村分别有4、 3个和2个; 空间扫描统计量法分析结果显示有1个患病率高值聚集区。 结论 结论 安乡县晚血分布存在局部空间自相关和一定的聚集性, 可根据这些分布特征, 合理安排防治资源, 从而更加有效地控制血吸虫病。

关键词: 晚期血吸虫病; 地理信息系统; 空间分布; 湖沼地区

Abstract:

Objective To explore the spatial distribution and pattern of advanced schistosomiasis in Anxiang County so as to provide the evidence for improving advanced schistosomiasis control. Methods Based on the geographic database of advanced schistosomiasis distribution at the village level in Anxiang County,Hunan Province,the spatial autocorrelation analysis and spa? tial scan statistics were applied to analyze the spatial characteristics of distribution of advanced schistosomiasis. Results The global Moran?? s I of prevalence rate of advanced schistosomiasis was 0.06 (P > 0.05) and there was no spatial auto?correlation as a whole. The local spatial auto?correlation analysis showed that there were 9 villages with statistically significant LISA value (P < 0.05),among which existed high?high, low?high and high?low types of auto?correlation model. The results of SaTScan statistics was the same as local spatial auto?correlation analysis and showed the existence of one cluster area. Conclusions There are local spatial auto?correlation and spatial aggregation of advanced schistosomiasis in Anxiang County. According to the distribution char? acteristics,we can assign resource more reasonably and control schistosomiasis more effectively.

Key words: Advanced schistosomiasis;Geographic information system (GIS);Spatial distribution;Marshland and lake re? gions

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