Surveillance in easy to access population subgroups as a tool for evaluating malaria control progress: A systematic review.
Surveillance in easy to access population subgroups as a tool for evaluating malaria control progress: A systematic review.
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DOI：
10.1371/journal.pone.0183330
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Terlouw DJ
中科院分区：
文献类型：
--
作者：
Sesay SSS;Giorgi E;Diggle PJ;Schellenberg D;Lalloo DG;Terlouw DJ
规划管理人员、决策者和科学家强调，监测系统需要产生有针对性的、数据驱动的、反应迅速的控制工作，以加速和维持减少疟疾传播。与入户调查相比，使用易于获取的人口分组（eag）进行监测可节省相当大的成本，因为调查对象的识别和选择简化了，所需人员更少，后勤也更简单。我们回顾了现有文献，验证了由EAGs得出的疟疾控制进展关键指标的估计，并描述了处理可能发生的特定背景偏差的选择。对2016年12月31日之前报告证实EAG调查中疟疾控制指标估计值的所有文件进行文献检索。通过交叉参考选定的记录、其他适用的政策文件和灰色文献，确定了其他记录。剔除重复后，评估了13180篇摘要，筛选出2653篇符合条件的涉及eeg监测的摘要，其中29篇全文文章被选中进行详细综述。选择用于系统审查的九篇文章将卫生机构和学校调查的估计数与同一地理区域同一人口的同期样本的估计数进行了比较。对现有用于监测疟疾控制进展的EAGs文献的回顾表明，在探索使用EAGs的潜在方法和环境方面所做的努力很少；研究之间和研究内部对控制进展的估计精度存在很大差异，特别是对控制干预覆盖范围的估计。只有一项研究评估了eeg样本的地理空间代表性，或进行了地理空间分析来评估或控制缺乏地理空间代表性。两项研究试图通过控制多变量分析中的偏倚来测量偏倚程度或提高估计的精度；这只在一项研究中成功了。所观察到的估计准确性的变化可能是由选择和/或信息偏差引起的，这是由于EAGs的固有性质造成的。回顾的研究提供了对设计和分析方法的见解，可以用来限制偏倚。在区或分区规划层面对疟疾控制进展进行常规监测的EAGs效用将受到几个因素的驱动，包括是否需要用于衡量传播减少程度的连续点估计或用于跟踪“热点”的更精确的地理空间分布、可接受的精度程度、目标人群以及可用于监测的资源。新的地质统计分析和混合采样框架为克服偏见提供了机会，因此有理由重新探索利用地质特征分析进行疟疾监测和评价。
The need for surveillance systems generating targeted, data-driven, responsive control efforts to accelerate and sustain malaria transmission reduction has been emphasized by programme managers, policy makers and scientists. Surveillance using easy-to-access population subgroups (EAGs) may result in considerable cost saving compared to household surveys as the identification and selection of individuals to be surveyed is simplified, fewer personnel are needed, and logistics are simpler. We reviewed available literature on the validation of estimates of key indicators of malaria control progress derived from EAGs, and describe the options to deal with the context specific bias that may occur. A literature search was conducted of all documents reporting validation of estimates of malaria control indicators from EAG surveys before the 31st of December 2016. Additional records were identified through cross-reference from selected records, other applicable policy documents and grey literature. After removal of duplicates, 13, 180 abstracts were evaluated and 2,653 eligible abstracts were identified mentioning surveillance in EAGs, of which 29 full text articles were selected for detailed review. The nine articles selected for systematic review compared estimates from health facility and school surveys with those of a contemporaneous sample of the same population in the same geographic area. Review of the available literature on EAGs suitable for surveillance of malaria control progress revealed that little effort has been made to explore the potential approach and settings for use of EAGs; and that there was wide variation in the precision of estimates of control progress between and within studies, particularly for estimates of control intervention coverage. Only one of the studies evaluated the geospatial representativeness of EAG samples, or carried out geospatial analyses to assess or control for lack of geospatial representativeness. Two studies attempted to measure the degree of bias or improve the precision of estimates by controlling for bias in a multivariate analysis; and this was only successful in one study. The observed variability in accuracy of estimates is likely to be caused by selection and/or information bias due to the inherent nature of EAGs. The reviewed studies provided insight into the design and analytical approaches that could be used to limit bias. The utility EAGs for routine surveillance of progress in malaria control at the district or sub-district programmatic level will be driven by several factors including whether serial point estimates to measure transmission reduction or more precise geospatial distribution to track ‘hot-spots’ is required, the acceptable degree of precision, the target population, and the resources available for surveillance. The opportunities offered by novel geostatistical analyses and hybrid sampling frames to overcome bias justify a renewed exploration of use of EAGs for malaria monitoring and evaluation.
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