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A grid-based sampling design for household surveys in the absence of actionable sampling frames

A grid-based sampling design for household surveys in the absence of actionable sampling frames
A grid-based sampling design for household surveys in the absence of actionable sampling frames
Household surveys are a cost-effective data source for estimating health and demographic characteristics in low- and middle-income countries. These surveys involve sampling from a frame listing all the members of the population of interest. However, the listing needs to be complete, accurate, and up-to-date to draw samples that can be generalized to the entire population. A sampling frame generally consists of the enumeration areas established during the last national census, together with the associated population counts. However, these counts are often inaccurate because the national census is carried out on a decade basis. Outdated sampling frames are particularly critical in Africa, where five countries had their last census more than fifteen years ago. To tackle the absence of actionable sampling frames, we propose an original grid-based sampling design, embedding spatial sampling concepts into household surveys. We demonstrate our framework with a case study developed in the western part of the Democratic Republic of Congo (DRC). This country had its last national census in 1984, and the resulting sampling frame is still currently used in household surveys.
Darin, Edith
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Boo, Gianluca
d49f7aaa-6d95-4e36-b9be-e469911c4a3d
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Thomson, Dana
c6aa22a0-9ee2-4d86-9bd4-b3a8487eb15b
Darin, Edith
868fa688-2567-4dbd-aa12-3dcc91f2aa8d
Boo, Gianluca
d49f7aaa-6d95-4e36-b9be-e469911c4a3d
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Thomson, Dana
c6aa22a0-9ee2-4d86-9bd4-b3a8487eb15b

Darin, Edith, Boo, Gianluca, Tatem, Andrew and Thomson, Dana (2019) A grid-based sampling design for household surveys in the absence of actionable sampling frames. GEOMED 2019: XI international, interdisciplinary conference on spatial statistics, geographical epidemiology and geographical aspects of public health, , Glasgow, United Kingdom. 27 - 29 Aug 2020. 1 pp . (doi:10.13140/RG.2.2.31686.83524).

Record type: Conference or Workshop Item (Poster)

Abstract

Household surveys are a cost-effective data source for estimating health and demographic characteristics in low- and middle-income countries. These surveys involve sampling from a frame listing all the members of the population of interest. However, the listing needs to be complete, accurate, and up-to-date to draw samples that can be generalized to the entire population. A sampling frame generally consists of the enumeration areas established during the last national census, together with the associated population counts. However, these counts are often inaccurate because the national census is carried out on a decade basis. Outdated sampling frames are particularly critical in Africa, where five countries had their last census more than fifteen years ago. To tackle the absence of actionable sampling frames, we propose an original grid-based sampling design, embedding spatial sampling concepts into household surveys. We demonstrate our framework with a case study developed in the western part of the Democratic Republic of Congo (DRC). This country had its last national census in 1984, and the resulting sampling frame is still currently used in household surveys.

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More information

Published date: August 2019
Venue - Dates: GEOMED 2019: XI international, interdisciplinary conference on spatial statistics, geographical epidemiology and geographical aspects of public health, , Glasgow, United Kingdom, 2020-08-27 - 2020-08-29

Identifiers

Local EPrints ID: 442931
URI: http://eprints.soton.ac.uk/id/eprint/442931
PURE UUID: b176a52c-4447-46cd-850c-a4389665b2dd
ORCID for Edith Darin: ORCID iD orcid.org/0000-0002-8176-092X
ORCID for Gianluca Boo: ORCID iD orcid.org/0000-0002-4078-8221
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X
ORCID for Dana Thomson: ORCID iD orcid.org/0000-0002-9507-9123

Catalogue record

Date deposited: 03 Aug 2020 16:30
Last modified: 17 Mar 2024 04:00

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Contributors

Author: Edith Darin ORCID iD
Author: Gianluca Boo ORCID iD
Author: Andrew Tatem ORCID iD
Author: Dana Thomson ORCID iD

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