中国血吸虫病防治杂志 ›› 2016, Vol. 28 ›› Issue (6): 624-629,643.

• 论著 • 上一篇    下一篇

血吸虫病传播控制阶段湖沼型流行区传播风险时空分布特征研究

薛靖波1|夏尚1|张瑕2|胡合华2|王强1|周艺彪3|李石柱1*   

  1. 1 中国疾病预防控制中心寄生虫病预防控制所、世界卫生组织热带病合作中心、卫生部寄生虫病原与媒介生物重点实验室(上海 200025);2 湖北省江陵县血吸虫病防治所;3 复旦大学公共卫生学院
  • 出版日期:2016-12-11 发布日期:2016-12-11
  • 通讯作者: 李石柱
  • 作者简介:薛靖波|男|硕士|研究实习员。研究方向:空间流行病学
  • 基金资助:
    国家自然科学基金项目(81101280);国家传染病重大专项(2012ZX10004220, 2012ZX10004?201);高分遥感监测项目(10?Y30B11?9001?14/16);上海市公共卫生三年行动计划项目(GWIV?29);中英全球卫生项目(GHSP 202708);卫生部寄生虫病原与媒介生物学重点实验室资助课题(WSBKTKT2014 06); 2015-2016年度湖北省卫生计生血防专项(WJ2015XB023)

Pattern analysis of tempo-spatial distribution of schistosomiasis in marshland epidemic areas in stage of transmission control

XUE Jing-bo1|XIA Shang1|ZHANG Xia2|HU He-hua2|WANG Qiang1|ZHOU Yi-biao3|LI Shi-zhu1*   

  1. 1 National Institute of Parasitic Diseases|Chinese Center for Disease Control and Prevention|Key Laboratory of Parasite and Vec? tor Biology|Commission of Health and Family Planning|WHO Collaborating Center for Malaria|Schistosomiasis and Filaria? sis|Shanghai 200025|China;2 Jiangling Station of Schistosomiasis Control|Hubei Province|China;3 School of Public Health|Fudan University|Shanghai|China
  • Online:2016-12-11 Published:2016-12-11
  • Contact: LI Shi?zhu

摘要: 目的 了解湖北省江陵县血吸虫病疫情的时空分布特征,识别风险区域,为湖沼型流行区在传播控制阶段防治血吸虫病提供科学依据。 方法 收集2009-2013年江陵县的血吸虫病疫情资料,结合空间位置信息构建数据库,进行空间分析。 结果 江陵县血吸虫病居民感染率由2009年的2.15%下降至2013年的0.63%,疫情降至历史最低水平。空间分析结果显示居民血吸虫感染率在空间分布上具有聚集性,在不同年份全局空间自相关指标Moran’s I值具有统计学意义。SaTScan和FleXScan两种时空扫描分析方法分别探测出18个和35个聚集区域。结论 湖北省江陵县2009-2013年血吸虫病居民感染率呈逐年稳中下降趋势,疫情存在空间聚集性,可根据血吸虫病疫情空间分布特征因地制宜采取防控策略和措施。

关键词: 血吸虫病;时空分布特征;热点分析;聚集性特征;江陵县

Abstract: Objective To investigate the tempo?spatial patterns of schistosomiasis in Jiangling County, Hubei Province, so as to identify the risk areas and provide the scientific evidence in following intervention plans for marshland epidemic areas in the stage of transmission control. Methods The schistosomiasis epidemiological data in Jiangling County from 2009 to 2013 together with the related geographical information were collected and analyzed. The tempo?spatial distribution patterns were analyzed by the spatial autocorrelation analysis and spatial clustering analysis. Results The human infection rate was decreased from 2.15% in 2009 to 0.63% in 2013, which was the historically low level. The results of tempo?spatial analysis showed that there were spatial clustering effects in human schistosomiasis infection for each of the years. The values of spatial autocorrelation index Moran’s I were statistically significant. Eighteen and thirty?five clusters were detected by using SatScan and FlexScan software, respectively. Conclusions From 2009 to 2013, the schistosomiasis endemic situation in Jiangling County presented a decline trend and reached the historical low level. The identified spatial clustering areas should be targeted as the prioritized areas for schistosomiasis control.

Key words: Schistosomiasis; Temporal?spatial distribution; Hotspot analysis; Clustering analysis; Jiangling County

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