江苏省疟疾流行地理信息系统预测模型的研究

目的 建立江苏省疟疾地理信息系统(GIS)数据库和疟疾流行GIS模型,对江苏省的疟疾流行区进行空间分析。方法 在ArcView3．0a软件中建立江苏省疟疾流行病学GIS数据库,从世界粮农组织的FAOCLIM气象资料库中提取出江苏省及其周边地区的气象数据,计算疟原虫生长发育累积度-日(TGDD),在Arc View3.0a软件支持下对TGDD进行空间分析。结果 获江苏省疟疾TGDD预测分布图,江苏省疟疾流行的程度由西向东逐渐减轻,并可分为3个地带;获江苏省14年疟疾平均发病率分布图,江苏省中部、西部地区疫情较重,江南太湖流域的苏、锡、常地区、南通及江苏北部边界少数县疫情较轻,其他地区的发病率介于两者之间,江苏省14年疟疾平均发病率分布图与江苏省疟疾TGDD预测分布图基本吻合。结论 基于TGDD的GIS预测模型可应用于江苏省疟疾流行的监测。

GIS prediction model of malaria transmission in Jiangsu province

Objectives To perform GIS spatial analysis on malaria transmission patterns in Jiangsu after setting up a malaria database and developing GIS model of malaria transmission in Jiangsu province. Methods The epidemiological GIS database of malaria in Jiangsu province was established using ArcView3 0a software. The climate data covering Jiangsu province and its peripheral area were extracted from the FAOCLIM database, the total growing degree days (TGDD) for Plasmodium vivax were calculated, and spatial distribution for TGDD was analyzed by ArcVeiw 3 0a. Results The predicted malaria distribution map based on TGDD was created, which showed that the transmission of malaria decreased gradually from west to east, which can be divided into three belts according to the degree of transmission. The 14 year mean morbidity distribution map of malaria in Jiangsu showed that the middle and west parts of Jiangsu is the most serious endemic area. The morbidity in the areas along the Taihu valley, such as Suzhou, Wuxi and Changzhou, as well as Nantong and a few of northern counties are the lowest. The morbidity of other places is at the middle level. The 14 year mean morbidity distribution map of malaria is correlated with predicted malaria distribution map for TGDD. Conclusion It is possible to monitor the malaria transmission by GIS predicted model based on TGDD.