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首页> 外文期刊>The American Journal of Tropical Medicine and Hygiene >Bayesian spatial risk prediction of Schistosoma mansoni infection in western Cote d'Ivoire using a remotely-sensed digital elevation model.
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Bayesian spatial risk prediction of Schistosoma mansoni infection in western Cote d'Ivoire using a remotely-sensed digital elevation model.

机译:使用遥感数字高程模型对科特迪瓦西部曼氏血吸虫感染的贝叶斯空间风险预测。

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摘要

An important epidemiologic feature of schistosomiasis is the focal distribution of the disease. Thus, the identification of high-risk communities is an essential first step for targeting interventions in an efficient and cost-effective manner. We used a remotely-sensed digital elevation model (DEM), derived hydrologic features (i.e., stream order, and catchment area), and fitted Bayesian geostatistical models to assess associations between environmental factors and infection with Schistosoma mansoni among more than 4,000 school children from the region of Man in western Cote d'Ivoire. At the unit of the school, we found significant correlations between the infection prevalence of S. mansoni and stream order of the nearest river, water catchment area, and altitude. In conclusion, the use of a freely available 90 m high-resolution DEM, geographic information system applications, and Bayesian spatial modeling facilitates risk prediction for S. mansoni, and is a powerful approach for risk profiling of other neglected tropical diseases that are pervasive in the developing world.
机译:血吸虫病的重要流行病学特征是该病的病灶分布。因此,识别高危社区是以有效和具有成本效益的方式针对干预措施的重要的第一步。我们使用了遥感数字高程模型(DEM),派生的水文特征(即河流秩序和集水区),并拟合了贝叶斯地统计学模型,以评估环境因素与曼氏血吸虫感染之间的关联,该研究涉及4,000多名学龄儿童。科特迪瓦西部的曼地区。在学校的单位中,我们发现曼氏沙门氏菌的感染率与最近的河流,集水区和海拔高度的溪流次序之间存在显着的相关性。总之,使用免费提供的90 m高分辨率DEM,地理信息系统应用程序和贝叶斯空间模型有助于对曼氏沙门氏菌进行风险预测,并且是对其他普遍存在于热带地区的被忽视热带病进行风险分析的有力方法。发展中国家。

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