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Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda.

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gridded population datasets and "population" or "household" "survey" reports, and solicited additional published and unpublished sources from colleagues.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.

SUBMITTER: Thomson DR

PROVIDER: S-EPMC7488014 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda.

Thomson Dana R DR Rhoda Dale A DA Tatem Andrew J AJ Castro Marcia C MC

International journal of health geographics 20200909 1

<h4>Introduction</h4>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 popul ...[more]

PMID: 32907588

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Project description:Household survey data are collected by governments, international organizations, and companies to prioritize policies and allocate billions of dollars. Surveys are typically selected from recent census data; however, census data are often outdated or inaccurate. This paper describes how gridded population data might instead be used as a sample frame, and introduces the R GridSample algorithm for selecting primary sampling units (PSU) for complex household surveys with gridded population data. With a gridded population dataset and geographic boundary of the study area, GridSample allows a two-step process to sample "seed" cells with probability proportionate to estimated population size, then "grows" PSUs until a minimum population is achieved in each PSU. The algorithm permits stratification and oversampling of urban or rural areas. The approximately uniform size and shape of grid cells allows for spatial oversampling, not possible in typical surveys, possibly improving small area estimates with survey results.We replicated the 2010 Rwanda Demographic and Health Survey (DHS) in GridSample by sampling the WorldPop 2010 UN-adjusted 100 m × 100 m gridded population dataset, stratifying by Rwanda's 30 districts, and oversampling in urban areas. The 2010 Rwanda DHS had 79 urban PSUs, 413 rural PSUs, with an average PSU population of 610 people. An equivalent sample in GridSample had 75 urban PSUs, 405 rural PSUs, and a median PSU population of 612 people. The number of PSUs differed because DHS added urban PSUs from specific districts while GridSample reallocated rural-to-urban PSUs across all districts.Gridded population sampling is a promising alternative to typical census-based sampling when census data are moderately outdated or inaccurate. Four approaches to implementation have been tried: (1) using gridded PSU boundaries produced by GridSample, (2) manually segmenting gridded PSU using satellite imagery, (3) non-probability sampling (e.g. random-walk, "spin-the-pen"), and random sampling of households. Gridded population sampling is in its infancy, and further research is needed to assess the accuracy and feasibility of gridded population sampling. The GridSample R algorithm can be used to forward this research agenda.

Project description:BackgroundHousehold surveys are the main source of demographic, health and socio-economic data in low- and middle-income countries (LMICs). To conduct such a survey, census population information mapped into enumeration areas (EAs) typically serves a sampling frame from which to generate a random sample. However, the use of census information to generate this sample frame can be problematic as in many LMIC contexts, such data are often outdated or incomplete, potentially introducing coverage issues into the sample frame. Increasingly, where census data are outdated or unavailable, modelled population datasets in the gridded form are being used to create household survey sampling frames.MethodsPreviously this process was done by either sampling from a set of the uniform grid cells (UGC) which are then manually subdivided to achieve the desired population size, or by sampling very small grid cells then aggregating cells into larger units to achieve a minimum population per survey cluster. The former approach is time and resource-intensive as well as results in substantial heterogeneity in the output sampling units, while the latter can complicate the calculation of unbiased sampling weights. Using the context of Somalia, which has not had a full census since 1987, we implemented a quadtree algorithm for the first time to create a population sampling frame. The approach uses gridded population estimates and it is based on the idea of a quadtree decomposition in which an area successively subdivided into four equal size quadrants, until the content of each quadrant is homogenous.ResultsThe quadtree approach used here produced much more homogeneous sampling units than the UGC (1 × 1 km and 3 × 3 km) approach. At the national and pre-war regional scale, the standard deviation and coefficient of variation, as indications of homogeneity, were calculated for the output sampling units using quadtree and UGC 1 × 1 km and 3 × 3 km approaches to create the sampling frame and the results showed outstanding performance for quadtree approach.ConclusionOur approach reduces the manual burden of manually subdividing UGC into highly populated areas, while allowing for correct calculation of sampling weights. The algorithm produces a relatively homogenous population counts within the sampling units, reducing the variation in the weights and improving the precision of the resulting estimates. Furthermore, a protocol of creating approximately equal-sized blocks and using tablets for randomized selection of a household in each block mitigated potential selection bias by enumerators. The approach shows labour, time and cost-saving and points to the potential use in wider contexts.

Project description:BackgroundDespite the increasing mobilization of researchers and funding organizations around knowledge translation (KT) in Canada and elsewhere, many questions have been only partially answered, particularly in the field of population health. This article presents the results of a systematic process to draw out possible avenues of collaboration for researchers, practitioners and decision-makers who work in the area of KT. The main objective was to establish a research agenda on knowledge translation in population health.MethodsUsing the Concept Mapping approach, the research team wanted to identify priority themes for the development of research on KT in population health. Mapping is based on multivariate statistical analyses (multidimensional scaling and hierarchical cluster analysis) in which statements produced during a brainstorming session are grouped in weighted clusters. The final maps are a visual representation of the priority themes of research on KT. Especially designed for facilitating consensus in the understanding and organization of various concepts, the Concept Mapping method proved suitable for achieving this objective.ResultsThe maps were produced by 19 participants from university settings, and from institutions within the health and social services network. Three main perspectives emerge from this operation: (1) The evaluation of the effectiveness of KT efforts is one of the main research priorities; (2) The importance of taking into consideration user contexts in any KT effort; (3) The challenges related to sharing power for decision-making and action-taking among various stakeholder groups. These perspectives open up avenues of collaboration for stakeholders who are involved in research on KT. Besides these three main perspectives, the concept maps reveal three other trends which should be emphasized.ConclusionThe Concept Mapping process reported in this article aimed to provoke collective reflection on the research questions that should be studied, in order to foster coherence in research activities in the field of population health. Based on this, it is appropriate to continue to support the development of research projects in KT and the formation of research teams in this field. Research on KT must lead to concrete outcomes within communities that are interested in the question.

Project description:Background: The negative effects of sedentary behavior (SB) on public health have been extensively documented. A large number of studies have demonstrated that high prevalence of SB is a critical factor of all-cause mortality. Globally, the frequency of SB research has continued to rise, but little is known about SB in the Chinese population. Therefore, this review was conducted to scope the research situation and to fill the gaps related to the effects of SB in the Chinese population. Methods: Using a scoping review based on York methodology, a comprehensive search of published journal articles and grey literature was carried out through 12 databases. The literature research was conducted by two authors in July 2019, and included journal articles that targeted on the Chinese population were published between 1999 and 2019. The two authors screened the records independently and included those research topics related to SB in the Chinese population. Results: The number of included studies increased from 1 to 29 per year during the analyzed period, during which, a remarkable climb happened from 8 in 2013 to 19 in July 2019. Out of the 1303 screened studies, a total of 162 studies (81 English and 81 Chinese journal articles) met the inclusion criteria in this review. Most of the included studies (66.0%) reported the overall estimated prevalence of SB, in which, 43.2% of studies reported the average time of SB, and 40.0% of studies reported the cutoff point of SB. Besides this, 54.9% and 23.5% of studies focused on the outcomes and correlates/determinants of SB, and the proportions of studies based on testing the validation of measurement tools and on interventions were 3.7% and 4.9%, respectively. Nearly all of the reviewed articles used data from cross-sectional studies (75.9%) and longitudinal studies (13.6%), while intervention trials are less developed. The majority of the studies (64.8%) used self-reported surveys, and only 3.7% studies used device-based measurement tools. Furthermore, 35.8% of the included studies were focused on children and adolescents, while only a few studies investigated infants/toddlers and older adults. Both female and male were examined in most studies, and non-clinical populations were investigated in the context of SB in a relatively large number of studies. Conclusions: The number of research articles on SB in the Chinese population published per year has increased year by year, indicating a growing interest in this research area. More studies using population subgroup samples are needed, particularly among infants/toddlers, older adults, and clinical populations. To provide stronger evidence of the determinants and outcomes of SB, longitudinal studies using device-based measures of SB are required.

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Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda.

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Gridded population survey sampling: a systematic scoping review of the field and strategic research agenda.

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