钱海坤, 杨鹏, 张奕, 王小莉, 段玮, 王全意. 2005 - 2010年北京市猩红热发病时空扫描分析[J]. 疾病监测, 2011, 26(6): 435-438. DOI: 10.3784/j.issn.1003-9961.2011.06.006
引用本文: 钱海坤, 杨鹏, 张奕, 王小莉, 段玮, 王全意. 2005 - 2010年北京市猩红热发病时空扫描分析[J]. 疾病监测, 2011, 26(6): 435-438. DOI: 10.3784/j.issn.1003-9961.2011.06.006
QIAN Hai-kun, YANG Peng, ZHANG Yi, WANG Xiao-li, DUAN Wei, WANG Quan-yi. Spatial-temporal scan statistic on scarlet fever cases in Beijing, 2005 - 2010[J]. Disease Surveillance, 2011, 26(6): 435-438. DOI: 10.3784/j.issn.1003-9961.2011.06.006
Citation: QIAN Hai-kun, YANG Peng, ZHANG Yi, WANG Xiao-li, DUAN Wei, WANG Quan-yi. Spatial-temporal scan statistic on scarlet fever cases in Beijing, 2005 - 2010[J]. Disease Surveillance, 2011, 26(6): 435-438. DOI: 10.3784/j.issn.1003-9961.2011.06.006

2005 - 2010年北京市猩红热发病时空扫描分析

Spatial-temporal scan statistic on scarlet fever cases in Beijing, 2005 - 2010

  • 摘要: 目的 探讨2005 - 2010年北京市猩红热发病时空分布特征,掌握高发重点区域,为预防控制提供理论依据。 方法 利用SaTScan 9.0软件进行时空扫描分析,通过ArcGIS 9.3软件呈现猩红热时空聚集区域。 结果 北京市猩红热在2005年4月至2008年1月期间较其他时间高发,为最可能聚集发病的时间段(相对危险度RR=1.65,P=0.001)。单纯空间扫描分析和时空扫描分析均发现北京市西南方向的丰台区、大兴区、房山区和门头沟区,每年均存在猩红热发病异常增多,相对其他区域是一个最可能发病聚集区域(单纯空间扫描分析RR=1.78,P0.001;时空扫描分析RR=2.07,P0.001)。同时还发现西北方向的延庆县,昌平区较其他地区高发,为次要聚集区域(单纯空间扫描分析RR=1.50,P0.001)。另外还发现其他一些地区存在亚聚集状态。 结论 时空扫描分析方法可以非常好地应用于北京市猩红热高发重点区域分析,结合地理信息系统,能够更加直观、全面地展示了发病聚集区域,为以后开展针对性的预防控制措施,提供了科学参考依据。

     

    Abstract: Objective To understand the spatial and temporal distributions and the clustering areas of scarlet fever in Beijing from 2005 to 2010, and provide evidence for the disease prevention and control. Methods The spatial-temporal scan statistic was conducted with SaTScan9.0 software and scarlet fever clusters were showed with ArcGIS9.3 software. Results The incidence of scarlet fever was high from April 2005 to January 2007 in Beijing by temporal scan statistic . The most likely cluster was found in southwestern Beijing by both spatial scan statistic and spatial-temporal scan statistic with statistical significance (RR=1.78 for spatial scan statistic, P0.001, RR=2.07 for spatial-temporal scan statistic, P0.001). The secondary disease clusters were found in Yanqing and Changping counties in northwestern Beijing by spatial scan statistic (RR=1.50, P0.001). The sub-clusters were found in other areas. Conclusion Spatial-temporal scan statistic is fit to analyze the clusters of scarlet fever in Beijing. The clusters can be displayed intuitively and comprehensively by geographic information system, which could provide valuable information for the disease prevention and control.

     

/

返回文章
返回