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Subnational Variations in the Quality of Population Health Data: A Geospatial Analysis of Household Surveys in Africa

20 Pages Posted: 17 Jul 2023

See all articles by Valentin Seidler

Valentin Seidler

Vienna University of Economics and Business - Department of Economics

Chigozie Esdon Utazi

University of Southampton - WorldPop

Amelia Finaret

University of Edinburgh - Global Academy of Agriculture and Food Systems

Sebastian Luckeneder

Vienna University of Economics and Business - Department of Socioeconomics

Gregor Zens

International Institute for Applied Systems Analysis (IIASA)

Maksym Bondarenko

University of Southampton - WorldPop

Abigail Smith

Allegheny College - Department of Global Health Studies

Sarah Bradley

Saint Petersburg College - Independent Consultant

Andrew J. Tatem

University of Southampton - WorldPop

Patrick Webb

Tufts University

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Abstract

Background: In many low- and middle-income countries, household survey data help address health and development challenges and track achievements towards national objectives including the Sustainable Development Goals (SDGs). Such data are widely used and trusted. Yet users often lack critical information about the extent of data errors where it matters most for human wellbeing – at the district level, where health interventions are usually implemented. To assess the magnitude of such data problems, this study estimates the extent and types of errors in nationally representative household survey data from 33 African countries.

Methods: We conducted a comprehensive high-resolution geospatial analysis of household survey data from the most recent surveys of 33 countries across Africa between 2006 and 2019, using publicly available data from the Demographic and Health Surveys (DHS). We first calculated the prevalence of data errors by survey locations and then employed Bayesian model-based geostatistics using spatially explicit DHS data and covariates from gridded high-resolution datasets. Our model produced 5 × 5-km gridded estimates of three widely used health data quality indicators: age heaping, incomplete age records of interviewed women and biologically implausible height-for-age (HAZ) measures.

Findings: We report two important findings. First, the distribution of errors in survey data across and within Africa was systematic. Errors increased with remoteness. Second, moving beyond the DHS survey locations, our model found substantial heterogeneity in the distribution of errors on subnational levels. For example, the share of incomplete information of women’s age in Chad (national mean 66·1%) ranged from 91·8% (sd 2·5%) in southern Chad to only 6·8% (sd 2·2%) near the eastern border with Sudan.

Interpretation: This is the first study to estimate the subnational distribution of errors in household survey data at a high spatial resolution. Survey data quality degrades with increased remoteness, a phenomenon that adds to the vulnerability of remote populations. Our results illustrate the magnitude of data errors, contribute to SDG target 17.18 on reliable data availability, and promote better targeting of health interventions and data collection efforts within countries.

Funding: VS is supported by the Austrian National Bank’s Anniversary Fund Grant No. 18157. PW would like to acknowledge the support of Feed the Future Food Systems for Innovation Lab, funded by the United States Agency for International Development, Cooperative Agreement No. 7200AA21LE00001. AF is supported by the University of Edinburgh.

Declaration of Interest: The authors declare no competing interests.

Keywords: data quality, household surveys, measurement error, bias, population health surveys, demography, Bayesian analysis

Suggested Citation

Seidler, Valentin and Utazi, Chigozie Esdon and Finaret, Amelia and Luckeneder, Sebastian and Zens, Gregor and Bondarenko, Maksym and Smith, Abigail and Bradley, Sarah and Tatem, Andrew J. and Webb, Patrick, Subnational Variations in the Quality of Population Health Data: A Geospatial Analysis of Household Surveys in Africa. Available at SSRN: https://ssrn.com/abstract=4508419 or http://dx.doi.org/10.2139/ssrn.4508419

Valentin Seidler

Vienna University of Economics and Business - Department of Economics ( email )

Welthandelsplatz 1
D4
A-1020 Wien
Austria

HOME PAGE: http://https://www.wu.ac.at/vw1/m/dr-valentin-seidler-ba

Chigozie Esdon Utazi

University of Southampton - WorldPop ( email )

United Kingdom

Amelia Finaret (Contact Author)

University of Edinburgh - Global Academy of Agriculture and Food Systems ( email )

Sebastian Luckeneder

Vienna University of Economics and Business - Department of Socioeconomics ( email )

Gregor Zens

International Institute for Applied Systems Analysis (IIASA) ( email )

Maksym Bondarenko

University of Southampton - WorldPop ( email )

United Kingdom

Abigail Smith

Allegheny College - Department of Global Health Studies ( email )

Sarah Bradley

Saint Petersburg College - Independent Consultant ( email )

Andrew J. Tatem

University of Southampton - WorldPop ( email )

United Kingdom

Patrick Webb

Tufts University ( email )

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