Spatial modelling and the prediction of Loa loa risk:: Decision making under uncertainty
Spatial modelling and the prediction of Loa loa risk:: Decision making under uncertainty
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DOI：
10.1179/136485913x13789813917463
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发表时间：
2007-09-01
影响因子：
--
通讯作者：
Molyneux, D. H.
中科院分区：
文献类型：
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作者：
Diggle, P. J.;Thomson, M. C.;Molyneux, D. H.
在非洲工作的卫生决策者往往需要根据很少和不确定的信息为广大地理区域的数百万人采取行动。空间统计模型和贝叶斯推理现已被用来量化Loa loa区域环境风险图（非洲盘尾丝虫病控制方案目前将该图用作一个重要的决策工具）预测的不确定性。该方法允许表达的概率，给定的数据，一个特定的位置做或不超过预定义的高风险阈值，在该策略的变化，为提供抗蠕虫伊维菌素是必要的。
Health decision-makers working in Africa often need to act for millions of people over large geographical areas on little and uncertain information. Spatial statistical modelling and Bayesian inference have now been used to quantify the uncertainty in the predictions of a regional, environmental risk map for Loa loa ( a map that is currently being used as an essential decision tool by the African Programme for Onchocerciasis Control). The methodology allows the expression of the probability that, given the data, a particular location does or does not exceed a predefined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required.