地理学报

地理学报 ›› 2008, Vol. 63 ›› Issue (9): 981-993.doi: 10.11821/xb200809008

• 流域研究 • 上一篇    下一篇

广州SARS 流行的空间风险因子 与空间相关性特征

曹志冬1,2, 王劲峰1, 高一鸽1,2, 韩卫国3, 冯晓磊4, 曾光5   

  1. 1. 中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室, 北京100101;
    2. 中国科学院研究生院, 北京100039;
    3. Center for Spatial Information Science and System, George Mason University, USA;
    4. 河北师范大学资源与环境科学学院, 石家庄050016;
    5. 中国疾病预防控制中心, 北京100050
  • 收稿日期:2007-12-23 修回日期:2008-06-15 出版日期:2008-09-25 发布日期:2008-09-25
  • 通讯作者: 王劲峰, 研究员, 博导。
  • 作者简介:曹志冬(1978-), 男, 湖南益阳人, 博士研究生, 主要从事GIS 空间分析和、染病时空建模和空间抽样方面的 研究。E-mail: caozd@lreis.ac.cn
  • 基金资助:

    国家863 课题(2006AA12Z215,2007AA12Z241);国际科技合作项目(2007DFC20180);国家自然科学基金课 题(70571076, 40471111); 中国科学院方向性课题(KZCX2-YW-308); 国家科技支撑计划课题 (2006BAK01A13)

Risk Factor s and Autocor r elation Char acter istics on Sever e Acute Respir atory Syndrome in Guangzhou

CAO Zhidong1,2, WANG Jinfeng1,2, GAO Yige1,3, HAN Weiguo3,FENG Xiaolei4,ZENG Guang5   

  1. 1. State Key Laboratory of Resources & Environmental Information System, Institute of Geographic Sciences & Natural Resources Research, CAS, Beijing 100101, China;
    2. Graduate University of Chinese Academy of Sciences, Beijing 100039, China;
    3. Center for Spatial Information Science and System, George Mason University;
    4. Resources and Environment Science, Hebei Normal University, Shijiazhuang 050016, China;
    5. Chinese Center for Disease Control and Prevention), Beijing 100050, China
  • Received:2007-12-23 Revised:2008-06-15 Online:2008-09-25 Published:2008-09-25
  • Supported by:

    National High Technology Research and Development Program of China, No. 2006AA12Z215; No.2007AA12Z241; China International Science and Technology Cooperation, No. 2007DFC20180; National Natural Science Founation of China, No.70571076; No.40471111; Chinese Academy of Sciences Project, No.KZCX2-YW-308; National Key Science and Technology Project, No.2006BAK01A13

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被引次数

100

摘要：

传统的流行病学研究大多基于经典统计分析, 空间信息往往不能得到有效利用, 对传染病的空间风险因子与空间相关性特征的定量研究可以更科学地指导防控措施的制定。本文主要以2003 年广州市1277 例SARS 感染者的时空数据为研究对象, 利用kriging 空间插值技术与核心密度估计技术建立了1km×1km 精细格网单元上的发病率图, 并对人口密度、道路 交通、医院、商场、学校等9 个空间风险因子进行了深入研究, 结果表明这些风险因子均与 SARS 发病率有显著正相关, 严格控制这些风险因子可以有效防控SARS 流行。采用Moran's I 和LISA 统计指数定量分析了广州SARS 发病率的全局和局部的空间相关性特征及其时间变化规律, SARS 发病率的空间聚集性经历了由弱到强再到弱的变化过程, 发病率的高值聚集区域主要位于人口密度高、经济活跃、交通发达的城市中心地带, 且在整个SARS 流行过程中一直没有发生重心转移, 政府采取的防控措施成功的阻止了SARS 的进一步扩散传播, 但采取的就近收治感染者的措施导致了城市中心地带的传播风险一直居高不下。2003 年广州市突发的严重急性呼吸系统综合症事件为都市地区突发新型传染病的研究提供了一个标准样本, 本文研究可以为都市区突发SARS 或其他新型传染病的公共卫生应急预案提供科学依据。

关键词: 严重急性呼吸系统综合症, 空间风险因子, 发病率图, 广州

Abstract:

Most of the traditional epidemiological studies are based on the classic statistical analysis instead of spatial information. Spatial analysis of risk factor and autocorrelation characteristics of epidemic can guide scientific prevention and control measures. Spatio-temporal data of 1277 cases of infected persons in 2003 in Guangzhou are studied. Map of incidence rate based on 1 km×1 km grids is gained by kriging and kernel methods. Nine spatial risk factors, such as population density, traffic net, hospital, shopping mall, school, etc., are explored, results show that these risk factors are significantly correlated to incidence rate of SARS. Strict control measures to these risk factors can effectively prevent and control SARS epidemic. Global and local spatial autocorrelation characteristics are quantitatively measured with Moran's I and LISA statistics. Spatial cluster of incidence rate has experienced a weak-strong-weak process. High-high cluster areas are mainly in the center of Guangzhou city, where have high population density, economically active, and well-developed traffic net. The focus of high-high cluster areas did not transfer in the whole SARS epidemic process. The Government has taken successfully the prevention and control measures to prevent the further spread of SARS; however, the strategy of taking infectors to the nearest hospital contributed to the result that the spread risk has been high in the city centre. SARS incidence emerged in Guangzhou provides a sample for studying SARS and other unexpected new epidemics emerged in urban areas. Spatial autocorrelation analysis of SARS in Guangzhou provides a scientific basis for the emergency plan of the outbreak of SARS or other unexpected new epidemics in urban areas.

Key words: severe acute respiratory syndrome, spatial risk factor, map of incidence rate, Guangzhou