Gebre-Michael T, Malone J B, McNally K
Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia.
Parassitologia. 2005 Mar;47(1):135-44.
A risk assessment model was developed for onchocerciasis distribution and its control in Ethiopia using Geographic Information System (GIS) methods. GIS data analysis was done to generate 3 separate risk models using selected environmental features of (1) earth observing satellite data on Normalized Difference Vegetation Index (NDVI) and midday Land Surface Temperature (LST) prepared from AVHRR sensor data of the Global land 1-km project for the years 1992 and 1995, (2) FAO agroclimatic databases from the Crop Production System Zone (CPSZ) of the Intergovernmental Authority on Development (IGAD) sub-region of East Africa, and (3) a climate-based forecast index based on the growing degree days (GDD) and water budget concepts. Parasitological data used for the analysis were published and unpublished reports of onchocerciasis surveillance made between 1969 and 2000 in various parts of the country. Analysis of queries based on 1992 and 1995 annual wet and dry season data of the Global land 1-km project resulted in a predictive value of 95.1%, 94.0% and 96.3%, respectively, using data values extracted from buffers centered on sites above 5% prevalence. The model based on CPSZ data predicted an endemic area that best fit the distribution of sites over 5% prevalence; the query was based on CPSZ values of average altitude (442-2134 m), annual mean temperature (18-28 degrees C), annual rainfall (822-1980 mm), annual potential evapotranspiration (1264-1938 mm), rain minus potential evapotranspiration (-124 - 792 mm), average NDVI x 100 (2000-5000) and average terrain percent slope (9-34). The climate-based model based on GDD and water-budget predicted high risk to severe risk areas in the western and southwestern parts of the country. All three of the models predicted suitable areas for the transmission of onchocerciasis outside known endemic areas, suggesting the need for ground-based validation and potential application to current community-directed treatment programs with ivermectin (CDTI) for control of onchocerciasis in Ethiopia.
利用地理信息系统（GIS）方法，开发了一种用于盘尾丝虫病分布及其在埃塞俄比亚防治的风险评估模型。进行了GIS数据分析，以利用以下选定的环境特征生成3个单独的风险模型：（1）根据全球陆地1公里项目1992年和1995年的先进甚高分辨率辐射计（AVHRR）传感器数据编制的归一化植被指数（NDVI）和正午地表温度（LST）的地球观测卫星数据；（2）来自东非政府间发展管理局（伊加特）次区域作物生产系统区（CPSZ）的粮农组织农业气候数据库；（3）基于生长度日（GDD）和水分平衡概念的气候预测指数。用于分析的寄生虫学数据是1969年至2000年期间该国各地已发表和未发表的盘尾丝虫病监测报告。基于全球陆地1公里项目1992年和1995年的年度干湿季数据进行的查询分析，使用从患病率高于5%的地点为中心的缓冲区提取的数据值，预测值分别为95.1%、94.0%和96.3%。基于CPSZ数据的模型预测了一个流行区，该流行区最符合患病率超过5%的地点分布；查询基于CPSZ的平均海拔（442 - 2134米）、年平均温度（18 - 28摄氏度）、年降雨量（822 - 1980毫米）、年潜在蒸散量（1264 - 1938毫米）、降雨减去潜在蒸散量（-124 - 792毫米）、平均NDVI×100（2000 - 5000）和平均地形坡度百分比（9 - 34）的值。基于GDD和水分平衡的气候模型预测该国西部和西南部为高风险至严重风险区。所有这三个模型都预测了已知流行区以外适合盘尾丝虫病传播的区域，这表明需要进行地面验证，并可能应用于当前用伊维菌素进行的社区导向治疗项目（CDTI），以控制埃塞俄比亚的盘尾丝虫病。
