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基于高分辨率遥感的空间建模预测中国洞庭湖地区血吸虫病的潜在风险区域。

High-resolution remote sensing-based spatial modeling for the prediction of potential risk areas of schistosomiasis in the Dongting Lake area, China.

机构信息

National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention, National Center for Tropical Diseases Research, Key Laboratory of Parasite and Vector Biology, National Health Commission of China, WHO Collaborating Center for Tropical Diseases, Shanghai, 200025, People's Republic of China.

Hunan Institute of Schistosomiasis Control, Yueyang, 41400, People's Republic of China.

出版信息

Acta Trop. 2019 Nov;199:105102. doi: 10.1016/j.actatropica.2019.105102. Epub 2019 Jul 19.

Abstract

The geographical distribution of snail (i.e., the intermediate host of schistosomiasis) is consistent with that of endemic areas. The suitable snail habitus requires necessary environmental conditions for snail population. The high-resolution remote sensing provides an important tool for the spatio-temporal analysis of disease monitoring and prediction. This study conducted a typical schistosomiasis epidemic area in the marshland and lake regions along the Yangtze River, Yueyang City, Hunan Province of China. And three types of environmental factors, i.e., NDVI, soil moisture, and shortest distance to water body, associated with the geographical distribution of snail population, were extracted from the high-resolution remoting sensing data. The predicted distribution of snail habitus from the high-resolution environmental factors were compared with the data of annual program of snail survey. The results have shown that the application of high-resolution remote sensing can improve the accuracy of the modeled and predicted the potential risk areas of schistosomiasis, and may become an important tool for the ongoing national schistosomiasis control program.

摘要

螺(即血吸虫的中间宿主)的地理分布与流行区一致。适宜的螺栖息地需要有螺种群生存的必要环境条件。高分辨率遥感为疾病监测和预测的时空分析提供了重要工具。本研究以中国长江流域沿江湖泊沼泽地区的典型血吸虫病流行区湖南省岳阳市为例,从高分辨率遥感数据中提取了与螺种群地理分布相关的三种环境因素,即归一化植被指数、土壤湿度和与水体的最短距离。并将高分辨率环境因素预测的螺栖息地分布与年度螺调查数据进行了比较。结果表明,高分辨率遥感的应用可以提高模型的准确性,预测血吸虫病的潜在风险区域,可能成为正在进行的国家血吸虫病控制计划的重要工具。

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