Sabesan Shanmugavelu, Raju Hari Kishan K, Srividya AdiNarayanan, Das Pradeep Kumar
Vector Control Research Centre, Medical Complex, Indira Nagar, Pondicherry - 605 006, India.
Filaria J. 2006 Nov 9;5:12. doi: 10.1186/1475-2883-5-12.
The Global Programme to Eliminate Lymphatic Filariasis (GPELF) depends upon Mass Drug Administration (MDA) to interrupt transmission. Therefore, delimitation of transmission risk areas is an important step, and hence we attempted to define a geo-environmental risk model (GERM) for determining the areas of potential transmission of lymphatic filariasis.
A range of geo-environmental variables has been selected, and customized on GIS platform to develop GERM for identifying the areas of filariasis transmission in terms of "risk" and "non-risk". The model was validated through a 'ground truth study' following standard procedure using GIS tools for sampling and Immuno-chromotographic Test (ICT) for screening the individuals.
A map for filariasis transmission was created and stratified into different spatial entities, "risk' and "non-risk", depending on Filariasis Transmission Risk Index (FTRI). The model estimation corroborated well with the ground (observed) data.
The geo-environmental risk model developed on GIS platform is useful for spatial delimitation purpose on a macro scale.
全球消除淋巴丝虫病规划（GPELF）依靠大规模药物 administration（MDA）来阻断传播。因此，划定传播风险区域是重要的一步，所以我们试图定义一种地理环境风险模型（GERM）来确定淋巴丝虫病的潜在传播区域。
选择了一系列地理环境变量，并在GIS平台上进行定制，以开发GERM，用于根据“风险”和“非风险”识别丝虫病传播区域。该模型通过遵循标准程序的“实地验证研究”进行验证，使用GIS工具进行抽样，并使用免疫层析试验（ICT）对个体进行筛查。
创建了一张丝虫病传播地图，并根据丝虫病传播风险指数（FTRI）分为不同的空间实体，“风险”和“非风险”。模型估计与实地（观测）数据吻合良好。
在GIS平台上开发的地理环境风险模型对于宏观尺度的空间划定很有用。
