Use of weather data and remote sensing to predict the geographic and seasonal distribution of Phlebotomus papatasi in southwest Asia
Use of weather data and remote sensing to predict the geographic and seasonal distribution of Phlebotomus papatasi in southwest Asia
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DOI：
10.4269/ajtmh.1996.54.530
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发表时间：
1996-05-01
影响因子：
3.3
通讯作者：
Tucker, CJ
中科院分区：
文献类型：
--
作者：
Cross, ER;Newcomb, WW;Tucker, CJ
白蛉热和利什曼病是第二次世界大战期间部署到中东的军事人员中传染病发病的主要原因。最近，据报在西奈的联合国多国部队和观察员中有利什曼病。尽管有这些地方病的迹象，但在波斯湾战争的美国退伍军人中没有发现白蛉热病例，只有31例利什曼病病例。传播媒介帕帕塔斯白蛉在波斯湾的分布被认为高度依赖于环境条件，特别是温度和相对湿度。建立了一个计算机模型，以帕帕塔斯发生为因变量，气象数据为自变量。该模型的结果表明，最大的白蛉活动，因此白蛉热和利什曼原虫感染的最高风险发生在美国军队部署到波斯湾之前的春季/夏季月份。由于气象模型只产生气象站所在地点的发生概率信息，因此确定了每个气象站的高级甚高分辨率辐射计卫星遥感数据的归一化植被指数。根据按发生概率计算的NDVI水平频率的结果，确定了该矢量存在的NDVI水平范围。然后，计算机确定了所示归一化差异植被指数范围内的所有像素，并制作了一张计算机生成的帕帕塔斯可能分布图。由此产生的地图将分析范围扩大到没有气象站和文献中没有报告任何信息的地区，确定这些地区的病媒发生概率高或低。
Sandfly fever and leishmaniasis were major causes of infectious disease morbidity among military personnel deployed to the Middle East during World War II. Recently, leishmaniasis has been reported in the United Nations Multinational Forces and Observers in the Sinai. Despite these indications of endemicity, no cases of sandfly fever and only 31 cases of leishmaniasis have been identified among U.S. veterans of the Persian Gulf War. The distribution in the Persian Gulf of the vector, Phlebotomus papatasi, is thought to be highly dependent on environmental conditions, especially temperature and relative humidity. A computer model was developed using the occurrence of P. papatasi as the dependent variable and weather data as the independent variables. The results of this model indicated that the greatest sand fly activity and thus the highest risk of sandfly fever and leishmania infections occurred during the spring/summer months before U.S. troops were deployed to the Persian Gulf. Because the weather model produced probability of occurrence information for locations of the weather stations only, normalized difference vegetation index (NDVI) levels from remotely sensed Advanced Very High Resolution Radiometer satellites were determined for each weather station. From the results of the frequency of NDVI levels by probability of occurrence, the range of NDVI levels for presence of the vector was determined. The computer then identified all pixels within the NDVI range indicated and produced a computer-generated map of the probable distribution of P. papatasi. The resulting map expanded the analysis to areas where there were no weather stations and from which no information was reported in the literature, identifying these areas as having either a high or low probability of vector occurrence.