Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala
Abstract Background Population-representative household survey methods require up-to-date sampling frames and sample designs that minimize time and cost of fieldwork especially in low- and middle-income countries. Traditional methods such as multi-stage cluster sampling, random-walk, or spatial samp...
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| Format: | Article |
| Language: | English |
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BMC
2020-12-01
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| Series: | International Journal of Health Geographics |
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| Online Access: | https://doi.org/10.1186/s12942-020-00250-0 |
| _version_ | 1828940497173872640 |
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| author | Ann C. Miller Peter Rohloff Alexandre Blake Eloin Dhaenens Leah Shaw Eva Tuiz Francesco Grandesso Carlos Mendoza Montano Dana R. Thomson |
| author_facet | Ann C. Miller Peter Rohloff Alexandre Blake Eloin Dhaenens Leah Shaw Eva Tuiz Francesco Grandesso Carlos Mendoza Montano Dana R. Thomson |
| author_sort | Ann C. Miller |
| collection | DOAJ |
| description | Abstract Background Population-representative household survey methods require up-to-date sampling frames and sample designs that minimize time and cost of fieldwork especially in low- and middle-income countries. Traditional methods such as multi-stage cluster sampling, random-walk, or spatial sampling can be cumbersome, costly or inaccurate, leading to well-known biases. However, a new tool, Epicentre’s Geo-Sampler program, allows simple random sampling of structures, which can eliminate some of these biases. We describe the study design process, experiences and lessons learned using Geo-Sampler for selection of a population representative sample for a kidney disease survey in two sites in Guatemala. Results We successfully used Epicentre’s Geo-sampler tool to sample 650 structures in two semi-urban Guatemalan communities. Overall, 82% of sampled structures were residential and could be approached for recruitment. Sample selection could be conducted by one person after 30 min of training. The process from sample selection to creating field maps took approximately 40 h. Conclusion In combination with our design protocols, the Epicentre Geo-Sampler tool provided a feasible, rapid and lower-cost alternative to select a representative population sample for a prevalence survey in our semi-urban Guatemalan setting. The tool may work less well in settings with heavy arboreal cover or densely populated urban settings with multiple living units per structure. Similarly, while the method is an efficient step forward for including non-traditional living arrangements (people residing permanently or temporarily in businesses, religious institutions or other structures), it does not account for some of the most marginalized and vulnerable people in a population–the unhoused, street dwellers or people living in vehicles. |
| first_indexed | 2024-12-14T03:20:39Z |
| format | Article |
| id | doaj.art-4adf604009c64b40b5923e92f231fae1 |
| institution | Directory Open Access Journal |
| issn | 1476-072X |
| language | English |
| last_indexed | 2024-12-14T03:20:39Z |
| publishDate | 2020-12-01 |
| publisher | BMC |
| record_format | Article |
| series | International Journal of Health Geographics |
| spelling | doaj.art-4adf604009c64b40b5923e92f231fae12022-12-21T23:19:02ZengBMCInternational Journal of Health Geographics1476-072X2020-12-0119111010.1186/s12942-020-00250-0Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural GuatemalaAnn C. Miller0Peter Rohloff1Alexandre Blake2Eloin Dhaenens3Leah Shaw4Eva Tuiz5Francesco Grandesso6Carlos Mendoza Montano7Dana R. Thomson8Department of Global Health and Social Medicine, Harvard Medical SchoolDepartment of Global Health and Social Medicine, Harvard Medical SchoolEpicentreWuqu’ Kawoq, Maya Health AllianceWuqu’ Kawoq, Maya Health AllianceWuqu’ Kawoq, Maya Health AllianceEpicentreInstitute of Nutrition of Central America and Panama (Instituto de Nutrición de Centroamérica, INCAP), y PanamáDepartment of Social Statistics and Demography, University of SouthamptonAbstract Background Population-representative household survey methods require up-to-date sampling frames and sample designs that minimize time and cost of fieldwork especially in low- and middle-income countries. Traditional methods such as multi-stage cluster sampling, random-walk, or spatial sampling can be cumbersome, costly or inaccurate, leading to well-known biases. However, a new tool, Epicentre’s Geo-Sampler program, allows simple random sampling of structures, which can eliminate some of these biases. We describe the study design process, experiences and lessons learned using Geo-Sampler for selection of a population representative sample for a kidney disease survey in two sites in Guatemala. Results We successfully used Epicentre’s Geo-sampler tool to sample 650 structures in two semi-urban Guatemalan communities. Overall, 82% of sampled structures were residential and could be approached for recruitment. Sample selection could be conducted by one person after 30 min of training. The process from sample selection to creating field maps took approximately 40 h. Conclusion In combination with our design protocols, the Epicentre Geo-Sampler tool provided a feasible, rapid and lower-cost alternative to select a representative population sample for a prevalence survey in our semi-urban Guatemalan setting. The tool may work less well in settings with heavy arboreal cover or densely populated urban settings with multiple living units per structure. Similarly, while the method is an efficient step forward for including non-traditional living arrangements (people residing permanently or temporarily in businesses, religious institutions or other structures), it does not account for some of the most marginalized and vulnerable people in a population–the unhoused, street dwellers or people living in vehicles.https://doi.org/10.1186/s12942-020-00250-0Population-representative studySampling frameGuatemalaSimple random sampleSample selection |
| spellingShingle | Ann C. Miller Peter Rohloff Alexandre Blake Eloin Dhaenens Leah Shaw Eva Tuiz Francesco Grandesso Carlos Mendoza Montano Dana R. Thomson Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala International Journal of Health Geographics Population-representative study Sampling frame Guatemala Simple random sample Sample selection |
| title | Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala |
| title_full | Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala |
| title_fullStr | Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala |
| title_full_unstemmed | Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala |
| title_short | Feasibility of satellite image and GIS sampling for population representative surveys: a case study from rural Guatemala |
| title_sort | feasibility of satellite image and gis sampling for population representative surveys a case study from rural guatemala |
| topic | Population-representative study Sampling frame Guatemala Simple random sample Sample selection |
| url | https://doi.org/10.1186/s12942-020-00250-0 |
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