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A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings

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 f...

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Autores principales: Yu, Alexander T, Shakya, Rajani, Adhikari, Bikram, Tamrakar, Dipesh, Vaidya, Krista, Maples, Stace, Date, Kashmira, Bogoch, Isaac I, Bern, Caryn, Qamar, Farah, Yousafzai, Mohammad T, Garrett, Denise O, Longley, Ashley T, Hemlock, Caitlin, Luby, Stephen, Aiemjoy, Kristen, Andrews, Jason R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705878/
https://www.ncbi.nlm.nih.gov/pubmed/33258933
http://dx.doi.org/10.1093/cid/ciaa1310
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author Yu, Alexander T
Shakya, Rajani
Adhikari, Bikram
Tamrakar, Dipesh
Vaidya, Krista
Maples, Stace
Date, Kashmira
Bogoch, Isaac I
Bern, Caryn
Qamar, Farah
Yousafzai, Mohammad T
Garrett, Denise O
Longley, Ashley T
Hemlock, Caitlin
Luby, Stephen
Aiemjoy, Kristen
Andrews, Jason R
author_facet Yu, Alexander T
Shakya, Rajani
Adhikari, Bikram
Tamrakar, Dipesh
Vaidya, Krista
Maples, Stace
Date, Kashmira
Bogoch, Isaac I
Bern, Caryn
Qamar, Farah
Yousafzai, Mohammad T
Garrett, Denise O
Longley, Ashley T
Hemlock, Caitlin
Luby, Stephen
Aiemjoy, Kristen
Andrews, Jason R
author_sort Yu, Alexander T
collection PubMed
description 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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spelling pubmed-77058782020-12-07 A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings Yu, Alexander T Shakya, Rajani Adhikari, Bikram Tamrakar, Dipesh Vaidya, Krista Maples, Stace Date, Kashmira Bogoch, Isaac I Bern, Caryn Qamar, Farah Yousafzai, Mohammad T Garrett, Denise O Longley, Ashley T Hemlock, Caitlin Luby, Stephen Aiemjoy, Kristen Andrews, Jason R Clin Infect Dis Supplement Articles 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. Oxford University Press 2020-12-01 /pmc/articles/PMC7705878/ /pubmed/33258933 http://dx.doi.org/10.1093/cid/ciaa1310 Text en © The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Supplement Articles
Yu, Alexander T
Shakya, Rajani
Adhikari, Bikram
Tamrakar, Dipesh
Vaidya, Krista
Maples, Stace
Date, Kashmira
Bogoch, Isaac I
Bern, Caryn
Qamar, Farah
Yousafzai, Mohammad T
Garrett, Denise O
Longley, Ashley T
Hemlock, Caitlin
Luby, Stephen
Aiemjoy, Kristen
Andrews, Jason R
A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title_full A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title_fullStr A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title_full_unstemmed A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title_short A Cluster-based, Spatial-sampling Method for Assessing Household Healthcare Utilization Patterns in Resource-limited Settings
title_sort cluster-based, spatial-sampling method for assessing household healthcare utilization patterns in resource-limited settings
topic Supplement Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7705878/
https://www.ncbi.nlm.nih.gov/pubmed/33258933
http://dx.doi.org/10.1093/cid/ciaa1310
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