Bridging the Gap: GPSSample – An Innovative Tool for Enumeration and Sampling in Health Surveys

Global Gap: Updated population estimates and total households (HHs) per area, typically obtained through a census, are used to construct unbiased sampling frames necessary for accurate estimates in health surveys. These population and HH estimates are used to select a smaller representative sample of enumeration areas (EAs) to visit for a public health study. Several methods exist to select which HHs to visit at the EA level including systematic sampling (every n HH), geographically sampling structures using satellite imagery, segmenting an area, and mapping and listing all HHs in the selected EA. Accurate estimates are essential for public health programming and response; however, forty-two countries have not conducted a census for over a decade (United Nations Statistics Division 2024). Instead, programs often generate an accurate sampling frame by enumerating HHs within selected EAs obtaining answers to eligibility criteria, drawing a sample from this enumerated list, and navigating back to selected HHs. This requires considerable resources. To date, no free mobile-based application exists to streamline these processes

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-02
DOI
https://doi.org/10.5281/zenodo.14251032
Primary Topic
Data-Driven Disease Surveillance
Type
article
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article

Bridging the Gap: GPSSample – An Innovative Tool for Enumeration and Sampling in Health Surveys

Zenodo (CERN European Organization for Nuclear Research)
Data-Driven Disease Surveillance
article

Bridging the Gap: GPSSample – An Innovative Tool for Enumeration and Sampling in Health Surveys

article en

Abstract

Global Gap: Updated population estimates and total households (HHs) per area, typically obtained through a census, are used to construct unbiased sampling frames necessary for accurate estimates in health surveys. These population and HH estimates are used to select a smaller representative sample of enumeration areas (EAs) to visit for a public health study. Several methods exist to select which HHs to visit at the EA level including systematic sampling (every n HH), geographically sampling structures using satellite imagery, segmenting an area, and mapping and listing all HHs in the selected EA. Accurate estimates are essential for public health programming and response; however, forty-two countries have not conducted a census for over a decade (United Nations Statistics Division 2024). Instead, programs often generate an accurate sampling frame by enumerating HHs within selected EAs obtaining answers to eligibility criteria, drawing a sample from this enumerated list, and navigating back to selected HHs. This requires considerable resources. To date, no free mobile-based application exists to streamline these processes

Zenodo (CERN European Organization for Nuclear Research)
Georgia Institute of Technology (US), Agency for Toxic Substances and Disease Registry (US), The Task Force for Global Health (US), Georgia Tech Research Institute
Partnerships for the goals
Openalex Percentile: Top 47%
Data-Driven Disease Surveillance
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