中国媒介生物学及控制杂志 ›› 2015, Vol. 26 ›› Issue (5): 454-457.DOI: 10.11853/j.issn.1003.4692.2015.05.006

• 论著 • 上一篇    下一篇

Flexible空间扫描统计量在甘肃省自然疫源性疾病空间聚集性研究中的应用

魏孔福1, 刘新凤1, 任晓卫2, 刘东鹏1, 刘海霞1, 郑芸鹤1, 成瑶1, 蒋小娟1, 杨筱婷1, 李治平1, 苟发香1, 孟蕾1   

  1. 1 甘肃省疾病预防控制中心急性传染病防制科, 兰州 730000;
    2 兰州大学
  • 收稿日期:2015-04-28 出版日期:2015-10-20 发布日期:2015-10-20
  • 通讯作者: 孟蕾, Email: ccdcusc101@163.com
  • 作者简介:魏孔福, 男, 硕士, 主管技师, 主要从事传染病预防控制工作, Email: weikf2006@126.com
  • 基金资助:

    甘肃省卫生行业科研计划项目(GSWST 2012-06); 国家科技重大专项课题(2012ZX10004-208)

Study on the application of flexible spatial scan statistic to spatial aggregation of the natural foci diseases

WEI Kong-fu1, LIU Xin-feng1, REN Xiao-wei2, LIU Dong-peng1, LIU Hai-xia1, ZHENG Yun-he1, CHENG Yao1, JIANG Xiao-juan1, YANG Xiao-ting1, LI Zhi-ping1, GOU Fa-xiang1, MENG Lei1   

  1. 1 Gansu Center for Disease Control and Prevention, Lanzhou 730000, Gansu Province, China;
    2 Lanzhou University
  • Received:2015-04-28 Online:2015-10-20 Published:2015-10-20
  • Supported by:

    Supported by the Health Industry Scientific Research Projects in Gansu Province (No. GSWST 2012-06) and the Major National Science and Technology Projects of China (No. 2012ZX10004-208)

摘要:

目的 探讨甘肃省4种主要自然疫源性疾病空间分布特征, 掌握高发重点区域, 为疫情防控提供理论依据。方法 利用Flexible空间扫描统计量对甘肃省2009-2013年4种自然疫源性疾病进行空间扫描分析, 通过地理信息系统呈现空间聚集区域。结果 空间扫描结果显示, 甘肃省4种自然疫源性疾病具有明显的空间聚集区域。其中, 肾综合征出血热、布鲁氏菌病(布病)和炭疽主要集中在甘肃省东南部的湿润区, 呈现出东南多西北少的特点, 并且布病和炭疽高发区主要在农牧区。疟疾主要集中在甘肃省西部地区。结论 Flexible空间扫描软件与地理信息系统相结合可有效对甘肃省4种自然疫源性疾病的空间聚集性作出早期预警。

关键词: 自然疫源性疾病, 空间扫描统计, 地理信息系统, 早期预警

Abstract:

Objective To explore the spatial distribution of 4 natural foci diseases in Gansu province and provide theoretical basis for the diseases prevention and control. Methods Spatial clustering analysis was used to draw the higher incidence areas of 4 natural foci diseases from 2009 to 2013 in Gansu province, simultaneously, Geographic Information System(GIS) was also employed to visualize results of cluster detection tests. Results The results of the spatial clustering detection showed that the districts with spatial aggregation display a marked difference of 4 natural foci diseases. The hemorrhagic fever, brucellosis and anthrax mainly concentrated in the humid region in southeast of Gansu province, the cases were more prevalent in southeast and less in northwest. The brucellosis and anthrax high-risk areas mainly concentrated in the pastoral areas, while malaria high-risk areas mainly concentrated in western Gansu. Conclusion The early warning system based on flexible spatial scan statistic and geographical information system could work efficiently.

Key words: Natural foci diseases, Spatial scan statistic, Geographic information system, Early warning

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