Bayesian spatial risk prediction of Schistosoma mansoni infection in western Cote d'Ivoire using a remotely-sensed digital elevation model
Bayesian spatial risk prediction of Schistosoma mansoni infection in western Cote d'Ivoire using a remotely-sensed digital elevation model
复制标题
DOI：
10.4269/ajtmh.2007.76.956
复制
发表时间：
2007-05-01
影响因子：
3.3
通讯作者：
Utzinger, Juerg
中科院分区：
文献类型：
--
作者：
Beck-Woerner, Christian;Raso, Giovanna;Utzinger, Juerg
血吸虫病的一个重要流行病学特征是该病的病灶分布。因此，查明高风险社区是以有效和具有成本效益的方式有针对性地采取干预措施的重要第一步。我们使用了遥感数字高程模型（DEM），推导出水文特征（即，河流顺序和集水区），并拟合贝叶斯地质统计模型，以评估环境因素与科特迪瓦西部马恩地区4 000多名学童感染曼氏血吸虫之间的关联。在学校单元，我们发现感染率之间存在着显著的相关性。最近河流的mansoni和溪流顺序、集水区和海拔高度。总之，使用免费提供的90米高分辨率DEM，地理信息系统的应用，贝叶斯空间建模有利于风险预测的S。mansoni，是对发展中国家普遍存在的其他被忽视的热带疾病进行风险分析的有力方法。
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.