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Yu AT, Shakya R, Adhikari B, Tamrakar D, Vaidya K, Maples S, Date K, Bogoch II, Bern C, Qamar F, Yousafzai MT, Garrett DO, Longley AT, Hemlock C, Luby S, Aiemjoy K, Andrews JR. A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings. Clin Infect Dis 2020; 71:S239-S247. [PMID: 33258933 PMCID: PMC7705878 DOI: 10.1093/cid/ciaa1310] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Implementation of population-based surveys is resource intensive and logistically demanding, especially in areas with rapidly changing demographics and incomplete or no enumeration of the underlying population and their residences. To remove the need for pre-enumeration and to simplify field logistics for the population healthcare utilization survey used for the Surveillance for Enteric Fever in Asia Project in Nepal, we incorporated a geographic information system-based geosurvey and field mapping system into a single-stage cluster sampling approach. METHODS A survey was administered to ascertain healthcare-seeking behavior in individuals with recent suspected enteric fever. Catchment areas were based on residential addresses of enteric fever patients using study facilities; clusters were randomly selected from digitally created grids using available satellite images and all households within clusters were offered enrollment. A tablet-compatible geosurvey and mapping system that allowed for data-syncing and use in areas without cellular data was created using the ArcGIS suite of software. RESULTS Between January 2017 and November 2018, we surveyed 25 521 households in Nepal (16 769 in urban Kathmandu and 8752 in periurban Kavrepalanchok), representing 84 202 individuals. Overall, the survey participation rate was 90.9%, with geographic heterogeneity in participation rates within each catchment area. Areas with higher average household wealth had lower participation rates. CONCLUSION A geographic information system-based geosurvey and field mapping system allowed creation of a virtual household map at the same time as survey administration, enabling a single-stage cluster sampling method to assess healthcare utilization in Nepal for the Surveillance for Enteric Fever in Asia Project . This system removed the need for pre-enumeration of households in sampling areas, simplified logistics and could be replicated in future community surveys.
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Affiliation(s)
- Alexander T Yu
- Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, Stanford, California, USA
| | - Rajani Shakya
- Dhulikhel Hospital, Kathmandu University Hospital, Dhulikhel, Nepal
| | - Bikram Adhikari
- Dhulikhel Hospital, Kathmandu University Hospital, Dhulikhel, Nepal
| | - Dipesh Tamrakar
- Dhulikhel Hospital, Kathmandu University Hospital, Dhulikhel, Nepal
| | - Krista Vaidya
- Dhulikhel Hospital, Kathmandu University Hospital, Dhulikhel, Nepal
| | - Stace Maples
- Stanford Geospatial Center, Stanford University, Stanford, California, USA
| | - Kashmira Date
- Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Isaac I Bogoch
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Caryn Bern
- Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA
| | | | | | - Denise O Garrett
- Applied Epidemiology, Sabin Vaccine Institute, Washington, DC, USA
| | - Ashley T Longley
- Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- National Foundation for the Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Caitlin Hemlock
- Applied Epidemiology, Sabin Vaccine Institute, Washington, DC, USA
| | - Stephen Luby
- Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, Stanford, California, USA
| | - Kristen Aiemjoy
- Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, Stanford, California, USA
| | - Jason R Andrews
- Division of Infectious Diseases and Geographic Medicine, School of Medicine, Stanford University, Stanford, California, USA
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