Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda
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International Journal of Health Geographics Open Access
REVIEW
Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda Dana R. Thomson1,2* , Dale A. Rhoda3, Andrew J. Tatem2 and Marcia C. Castro4
Abstract Introduction: 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. Methods: 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gridded population datasets and "population" or "household" "survey" reports, and solicited additional published and unpublished sources from colleagues. Results: 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. Conclusions: 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. Keywords: Census, Survey design, Household survey, LMIC, WorldPop, LandScan Background Household surveys provide insight into the distribution of health, demographics, economics, and behaviours of populations, and are a primary resource for decision-making across low- and middle-income countries (LMICs). Household survey data are used to estimate *Correspondence: [email protected] 1 Department of Social Statistics and Demography, University of Southampton, Building 58, Southampton SO17 1BJ, UK Full list of author information is available at the end of the article
more than a quarter of the Sustainable Development Goal (SDG) indicators, to generate small area estimates (SAEs) of indicators that support decision-making in decentralized health systems [1], and to inform the distribution of development funding to, and within, LMICs. Nevertheless, as the use of household surveys has increased over the last 40 years, data accuracy
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