Using remote, spatial techniques to select a random household sample in a dispersed, semi-nomadic pastoral community: utility for a longitudinal health and demographic surveillance system.
Using remote, spatial techniques to select a random household sample in a dispersed, semi-nomadic pastoral community: utility for a longitudinal health and demographic surveillance system.
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DOI：
10.1186/s12942-015-0026-4
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发表时间：
2015-11-14
影响因子：
4.9
通讯作者：
Zwickle A
中科院分区：
文献类型：
--
作者：
Pearson AL;Rzotkiewicz A;Zwickle A
获得随机家庭样本可能既昂贵又具有挑战性。在坦桑尼亚农村一个由半游牧家庭组成的分散社区中，本研究旨在测试一种利用免费航空图像的替代方法。我们使用 Google 地球专业版（2041 年 2 月 7 日版本）中的“地标”固定了坦桑尼亚 Naitolia 的每个单体结构或 boma（化合物）。接下来，当地专家协助删除了错误分类的地标。然后使用随机数生成器选择随机样本。随机样本点被绘制出来并由调查点查员用来导航。我们在 34.5 个学生工作时间、3 个当地专家工作时间和 1.5 个学术工作时间中创建了一个空间样本框架和一个随机样本。挑战包括确定房屋是否被占用或被遗弃、制定地标包含协议以及航空图像本身的质量问题。在实地访问了 175 个样本点，其中 170 个（97%）是实际家庭。该方法的主要优点是： (a) 能够在农村和偏远地区生成稳健的随机样本； (b) 缺乏对现有外部人口数据来源的依赖； (c) 所需资金和时间水平相对较低。与现场生成家庭库存或家庭 GPS 跟踪相比，这种开发空间样本框架的方法高效且具有成本效益。在现场测试之前聘请当地专家审查样本框架大大提高了准确性。总体而言，这种方法是一种有前途的替代方法，可以替代昂贵且可能有偏差的家庭库存或所有家庭的现场 GPS 数据收集。
Obtaining a random household sample can be expensive and challenging. In a dispersed community of semi-nomadic households in rural Tanzania, this study aimed to test an alternative method utilizing freely available aerial imagery. We pinned every single-standing structure or boma (compound) in Naitolia, Tanzania using a ‘placemark’ in Google Earth Pro (version 7.1.2.2041). Next, a local expert assisted in removing misclassified placemarks. A random sample was then selected using a random number generator. The random sample points were mapped and used by survey enumerators to navigate. We created a spatial sample frame and a random sample in 34.5 student working hours, 3 local expert hours and 1.5 academic working hours. Challenges included determining whether homes were occupied or abandoned, developing a protocol for placemark inclusion and quality issues with the aerial imagery itself. In the field, 175 sample points were visited and 170 of these (97 %) were actual households. The primary advantages of this method were the: (a) ability to generate a robust random sample in a rural and remote area; (b) lack of reliance on existing, external population data sources; and (c) relatively low levels of funding and time required. This method to develop a spatial sample frame was efficient and cost-effective when compared to in-field generation of a household inventory or GPS tracking of households. Utilizing a local expert to review the sample frame prior to field testing greatly increased accuracy. Overall, this method is a promising alternative to expensive and possibly biased household inventories or in-field GPS data collection for all households.