Ripley′s L 指数与最近邻空间热点分析在流行病学标点地图分析中的应用

山东大学学报(医学版)

Ripley′s L 指数与最近邻空间热点分析在
流行病学标点地图分析中的应用

高杰¹，王志强²,邵琦¹,薛皓³,许桂春⁴,李学刚⁴,王洁贞¹，薛付忠¹

(1. 山东大学公共卫生学院流行病与卫生统计学研究所, 济南 250012;
2. 山东省疾病预防控制中心传染病防治所, 济南 250014;
3. 山东大学医学院, 济南 250012; 4. 莒南县卫生防疫站, 山东莒南 250000)

收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-03-16 发布日期:2009-03-16
通讯作者: 薛付忠

Ripley′s L index and the Nearest Neighbor ‘hot spots’ analysis in epidemiological spots map analysis

GAO Jie¹, WANG Zhiqiang², SHAO Qi¹, XUE Hao³, XU Guichun⁴,
LI Xuegang⁴, WANG Jiezhen¹, XUE Fuzhong¹

(1. Institute of Epidemiology and Biostatistics, School of Public Health, Shandong University, Jinan 250012, China;
2. Shandong Center for Disease Control and Prevention, Jinan 250014, China;
3. Medical College of Shandong University, Jinan 250012, China;
4. Junan Center for Disease Control and Prevention, Junan 250000, Shandong, China)

Received:1900-01-01 Revised:1900-01-01 Online:2009-03-16 Published:2009-03-16

摘要/Abstract

摘要： 目的探讨Ripley′s L(d) 指数与最近邻空间系统聚类分析在流行病学标点地图分析中的应用。方法采用实验流行病学的方法,以ArcGIS90为数据管理与分析平台,将Ripley′s L(d)指数分析与最近邻空间系统聚类分析结合,综合反应疾病空间异质性及其动态特征。结果实验疫区内,宿主鼠类第一聚集区平均半径为429?m;最强聚集区平均半径为1443?m;最大聚集区平均半径为8626?m。各村聚集“热点”数差别较大,其一阶波动范围为3～8个,二阶波动范围为0～1个;小家鼠第一聚集区平均半径为486?m;最强聚集区平均半径为2114?m;最大聚集区平均半径为9257?m。各村聚集“热点”数差别较大,其一阶波动范围为1～12个,二阶波动范围为0～2个;褐家鼠第一聚集区平均半径为500?m;最强聚集区平均半径为3271?m;最大聚集区平均半径为9386?m。结论在空间流行病学领域,将Ripley′s L(d)指数分析与最近邻空间系统聚类分析相结合,能够为阐明宿主鼠类的空间分布特征,控制HFRS传染源提供统计学依据。

关键词: Ripley′s L(d)指数, 聚类分析, 空间流行病学

Abstract:

To explore the application of Ripley′s L function and the nearest neighbor hierarchical clustering ‘hot spots’ analysis in epidemiological spots map analysis. MethodsArcGIS90 was used for data management and analysis. The experimental epidemiology method in combination with Ripley′s L function analysis and nearest neighbor spatial clustering analysis compositely reflected the disease spatial heterogeneity and its dynamic characters. ResultsThe average radius of the host rat was 429 meters, of the strongest cluster district was 1443 meters, and of the biggest cluster district of host rat was 8626 meters. The numbers of the “hot spot” in different villages greatly differed. The undulation range of the first order was 38 and of the second order was 01. The average radius of Mus norvegicus was 486 meters, of the strongest cluster district was 2114 meters, and of the biggest cluster district was 9257 meters. Numbers of the “hot spot” in different villages greatly differed. The undulation山东大学学报(医学版)47卷3期

高杰，等.Ripley′s L 指数与最近邻空间热点分析在流行病学标点地图分析中的应用[HT5”SS〗
range of the first order was 112 and of the second order was 02. The average radius of Rattus norvegicus was 500 meters, of the strongest cluster district was 3271 meters and of the biggest cluster district was 9386 meters. Numbers of the“hot spot” in different villages greatly differed. The undulation range of the first order was 311, and there was no cluster hot spot of the second order. ConclusionIn the spatial epidemiological field, Ripley′s L index analysis in combination with the nearest neighbor spatial clustering analysis can provide statistical evidence for clarifying the spatial distribution of the host rat and controlling the HFRS infection source.

Key words: Ripley′s L function, Cluster analysis, Spatial epidemiology

中图分类号:

R181

高杰1 ，王志强2 ,邵琦1 ,薛皓3 ,许桂春4 ,李学刚4 ,王洁贞1 ，薛付忠1
. Ripley′s L 指数与最近邻空间热点分析在
流行病学标点地图分析中的应用[J]. 山东大学学报(医学版), 2009, 47(03): 89-93.

GAO Jie¹, WANG Zhiqiang², SHAO Qi¹, XUE Hao³, XU Guichun⁴,
LI Xuegang⁴, WANG Jiezhen¹, XUE Fuzhong¹
. Ripley′s L index and the Nearest Neighbor ‘hot spots’ analysis in epidemiological spots map analysis[J]. JOURNAL OF SHANDONG UNIVERSITY (HEALTH SCIENCES), 2009, 47(03): 89-93.

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