Fine-scale malaria risk mapping from routine aggregated case data
Fine-scale malaria risk mapping from routine aggregated case data
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DOI：
10.1186/1475-2875-13-421
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发表时间：
2014-11-03
期刊：
影响因子：
3
通讯作者：
Gosling, Roland D.
中科院分区：
文献类型：
--
作者：
Sturrock, Hugh J. W.;Cohen, Justin M.;Gosling, Roland D.
背景：绘制疟疾风险地图是有效资源分配的一个组成部分。常规卫生设施数据很容易收集，但由于没有关于传播发生的位置的信息，它们对预测分集水区一级风险变化的有效性目前尚不清楚。方法：使用2011-2013年斯威士兰卫生设施级病例数据和精细的环境和生态变量，本研究探索使用分层贝叶斯建模框架将卫生设施集水区级别的风险地图缩小到精细尺度(1公里x 1公里)。结果：细尺度预测能够区分病例和假对照，其AUC值为0.84。当扩大到集水水平时，每个卫生机构的预测病例数与观察到的病例数大体一致，偏差很小，101个零病例卫生机构中有84个正确预测为零病例。结论：该方法有望帮助处于消除前和消除阶段的国家使用卫生设施水平的数据，在更精细的尺度上生成准确的风险地图。有必要在其他变速器环境中进一步验证，并评估该方法的操作价值。
Background: Mapping malaria risk is an integral component of efficient resource allocation. Routine health facility data are convenient to collect, but without information on the locations at which transmission occurred, their utility for predicting variation in risk at a sub-catchment level is presently unclear.Methods: Using routinely collected health facility level case data in Swaziland between 2011-2013, and fine scale environmental and ecological variables, this study explores the use of a hierarchical Bayesian modelling framework for downscaling risk maps from health facility catchment level to a fine scale (1 km x 1 km). Fine scale predictions were validated using known household locations of cases and a random sample of points to act as pseudo-controls.Results: Results show that fine-scale predictions were able to discriminate between cases and pseudo-controls with an AUC value of 0.84. When scaled up to catchment level, predicted numbers of cases per health facility showed broad correspondence with observed numbers of cases with little bias, with 84 of the 101 health facilities with zero cases correctly predicted as having zero cases.Conclusions: This method holds promise for helping countries in pre-elimination and elimination stages use health facility level data to produce accurate risk maps at finer scales. Further validation in other transmission settings and an evaluation of the operational value of the approach is necessary.