Subnational variations in the quality of household survey data in sub-Saharan Africa

Nationally representative household surveys collect geocoded data that are vital to tackling health and other development challenges in sub-Saharan Africa. Scholars and practitioners generally assume uniform data quality but subnational variation of errors in household data has never been investigated at high spatial resolution. Here, we explore within-country variation in the quality of most recent household surveys for 35 African countries at 5 × 5 km resolution and district levels. Findings show a striking heterogeneity in the subnational distribution of sampling and measurement errors. Data quality degrades with greater distance from settlements, and missing data as well as imprecision of estimates add to quality problems that can result in vulnerable remote populations receiving less than optimal services and needed resources. Our easy-to-access geospatial estimates of survey data quality highlight the need to invest in better targeting of household surveys in remote areas.

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Publication Details

Journal
Nature Communications
Published
2025-04-22
DOI
https://doi.org/10.1038/s41467-025-58776-5
Citations
13
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
17.60

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article

Subnational variations in the quality of household survey data in sub-Saharan Africa

C. Edson Utazi, Gregor Zens, Maksym Bondarenko, Sebastian Luckeneder et al.
13 citations
Nature Communications
Data-Driven Disease Surveillance
17.60
article

Subnational variations in the quality of household survey data in sub-Saharan Africa

C. Edson Utazi, Gregor Zens, Maksym Bondarenko, Sebastian Luckeneder, Sarah Bradley, Andrew J. Tatem, Valentin Seidler, Abigail R. Smith, Patrick Webb, Amelia B. Finaret
article en
13 citations

Abstract

Nationally representative household surveys collect geocoded data that are vital to tackling health and other development challenges in sub-Saharan Africa. Scholars and practitioners generally assume uniform data quality but subnational variation of errors in household data has never been investigated at high spatial resolution. Here, we explore within-country variation in the quality of most recent household surveys for 35 African countries at 5 × 5 km resolution and district levels. Findings show a striking heterogeneity in the subnational distribution of sampling and measurement errors. Data quality degrades with greater distance from settlements, and missing data as well as imprecision of estimates add to quality problems that can result in vulnerable remote populations receiving less than optimal services and needed resources. Our easy-to-access geospatial estimates of survey data quality highlight the need to invest in better targeting of household surveys in remote areas.

Nature CommunicationsVol. 16(1)
Vienna University of Economics and Business (AT), Allegheny College (US), Tufts University (US), International Institute for Applied Systems Analysis (AT), Central European University (AT), Independent Sector (US), University of Southampton (GB), University of Edinburgh (GB)
United States Agency for International Development, Austrian Science Fund, Oesterreichische Nationalbank
No poverty
Openalex Percentile: Top 1%
Data-Driven Disease Surveillance
17.60
DOIOpen Access PDFOpenAlex
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