广东省登革热及媒介种群的空间分布

Spatial distribution of dengue fever in Guangdong Province

目的 :探索登革热 (DF)流行和媒介种群的空间分布特征 ,为DF的防治和监测提供宏观的决策依据 .方法 :收集广东省 1995 / 2 0 0 1各市县的DF发病资料、同期的伊蚊媒介监测资料及广东省县界数字化地图 .在ArcGIS8.1空间分析软件支持下进行空间局部插值分析 ,借助于分布图的四个交叉核验指标以及分布图选取的两个原则选择最佳的DF发病和登革热媒介种群的分布图 .结果 :广东省 7个年度的DF流行及种群媒介的两种空间分布呈现地域一致性 ,呈现相对稳定的高、低、近无的三类区域分布状况 ,并且存在较明显的稳定的分界线 .7个年度的交叉核验平均值分别为 :DF发病的平均预测误差 (ME)、估计的方差 (RMSE)、平均标准误 (ASE)、预测误差的变异程度 (RMSSE)依次为 0 .0 12 2 ,0 .36 2 5 ,0 .4 133和 0 .9192 ;种群媒介的ME ,RMSE ,ASE ,RMSSE依次为 0 .0 14 3,0 .4 15 5 ,0 .16 5 3和 0 .9398.结论 :Kriging方法描述DF空间分布特征 ,可为DF的宏观的监测、预测。

AIM: To explore the spatial distribution characteristics of dengue fever prevalence and vector population so as to provide data for macroscopical decision making of surveillance and control. METHODS: Dengue fever data from all the cities and counties in Guangdong Province were collected from 1995 to 2001. Also collected were aedes vector data and the digitized map of Guangdong Province divided by county boundary in the same period of time. The distribution map of dengue fever and vector population was produced by spatial local interpolation analysis using theArcGIS8.1 software. The distribution map was finalized based on the Cross Validation index and two principles for comparison between different maps. RESULTS: The transmission intensity of dengue fever and vector population distribution map in Guangdong Province presented three relatively stable distributing status, viz.: high incidence area, low incidence area and almost none incidence area. The spatial distribution of dengue fever and vector aedes share the same distribution area, with a clear boundary. Seven years’ average cross validation index of mean prediction error (ME), root mean square error (RMSE), average standard error (ASE) and root mean square standardized error (RMSSE) of dengue fever morbidity was 0.0122, 0.3625 , 0.4133 and 0.9192. The index of vector population was 0.0143, 0.4155, 0.1653 and 0.9398 respectively. CONCLUSION : Kriging is a good method in producing the spatial distribution map of dengue fever and vector. On the basis of conventional epidemiology and view of geostatistics and GIS (Geographical Information Systems), Kriging can provide reliable evidence for dengue’s surveillance, forecast, control and macroscopical decision making.