PDF(Sci-hub)
Abstract：
In low- and middle-income countries (LMICs), household survey data are a main source of information for planning, evaluation, and decision-making. Standard surveys are based on censuses, however, for many LMICs it has been more than 10 years since their last census and they face high urban growth rates. Over the last decade, survey designers have begun to use modelled gridded population estimates as sample frames. We summarize the state of the emerging field of gridded population survey sampling, focussing on LMICs.
We performed a systematic scoping review in Scopus of specific gridded population datasets and \"population\" or \"household\" \"survey\" reports, and solicited additional published and unpublished sources from colleagues.
We identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, some survey teams interviewed all households in each cluster or segment, and others sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation.
For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings.
We performed a systematic scoping review in Scopus of specific gridded population datasets and \"population\" or \"household\" \"survey\" reports, and solicited additional published and unpublished sources from colleagues.
We identified 43 national and sub-national gridded population-based household surveys implemented across 29 LMICs. Gridded population surveys used automated and manual approaches to derive clusters from WorldPop and LandScan gridded population estimates. After sampling, some survey teams interviewed all households in each cluster or segment, and others sampled households from larger clusters. Tools to select gridded population survey clusters include the GridSample R package, Geo-sampling tool, and GridSample.org. In the field, gridded population surveys generally relied on geographically accurate maps based on satellite imagery or OpenStreetMap, and a tablet or GPS technology for navigation.
For gridded population survey sampling to be adopted more widely, several strategic questions need answering regarding cell-level accuracy and uncertainty of gridded population estimates, the methods used to group/split cells into sample frame units, design effects of new sample designs, and feasibility of tools and methods to implement surveys across diverse settings.
摘要：
在低收入和中等收入国家(LMICs)，家庭调查数据是规划的主要信息来源，评估，和决策。标准调查基于人口普查，然而,对于许多低收入国家来说，自上次人口普查以来已经超过10年，他们面临着高城市增长率。在过去的十年里，调查设计者已经开始使用模型化的网格化人口估计作为样本框架。我们总结了网格化人口调查抽样这一新兴领域的现状，专注于LMIC。
我们在Scopus中对特定的网格化人口数据集和“人口”或“家庭”报告进行了系统的范围审查，并征求同事的其他已发表和未发表的资料。
我们确定了在29个低收入国家中实施的43个国家和国家以下基于人口的网格化家庭调查。网格人口调查使用自动和手动方法从WorldPop和LandScan网格人口估计中得出聚类。取样后,一些调查小组采访了每个集群或细分市场中的所有家庭，其他人从较大的集群中抽取了家庭样本。选择网格化人口调查群集的工具包括GridSampleR包，地理采样工具，和GridSample.org。在田野里,网格化人口调查通常依赖于基于卫星图像或OpenStreetMap的地理准确地图，以及用于导航的平板电脑或GPS技术。
为了更广泛地采用网格化的人口调查抽样，关于网格化人口估计的细胞级准确性和不确定性，需要回答几个战略问题，用于将细胞分组/分割为样品框架单元的方法，新样本设计的设计效果，以及跨不同环境实施调查的工具和方法的可行性。
我们在Scopus中对特定的网格化人口数据集和“人口”或“家庭”报告进行了系统的范围审查，并征求同事的其他已发表和未发表的资料。
我们确定了在29个低收入国家中实施的43个国家和国家以下基于人口的网格化家庭调查。网格人口调查使用自动和手动方法从WorldPop和LandScan网格人口估计中得出聚类。取样后,一些调查小组采访了每个集群或细分市场中的所有家庭，其他人从较大的集群中抽取了家庭样本。选择网格化人口调查群集的工具包括GridSampleR包，地理采样工具，和GridSample.org。在田野里,网格化人口调查通常依赖于基于卫星图像或OpenStreetMap的地理准确地图，以及用于导航的平板电脑或GPS技术。
为了更广泛地采用网格化的人口调查抽样，关于网格化人口估计的细胞级准确性和不确定性，需要回答几个战略问题，用于将细胞分组/分割为样品框架单元的方法，新样本设计的设计效果，以及跨不同环境实施调查的工具和方法的可行性。
