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Advances in small area population estimation in the absence of national census data

Advances in small area population estimation in the absence of national census data
Advances in small area population estimation in the absence of national census data
Population data at small area scales are essential for effective decision-making, affecting public health, disaster response, and resource allocation, amongst other issues. While national censuses remain the foundational source of population data, they may face challenges such as high cost, infrequency, and coverage gaps, which can hinder timely data availability. Geospatial statistical approaches to address these challenges using limited microcensus surveys have been demonstrated, and the field has advanced substantially in recent years, with significant developments in both data sources and modelling methodologies. New approaches now enable the use of routine health intervention campaign data, improved satellite-derived settlement mapping, and novel Bayesian frameworks to produce high-quality small area population estimates where traditional enumeration is difficult or outdated. Various countries are increasingly applying these techniques to support census operations, health program planning, and humanitarian response. This Perspective reviews recent advances in ‘bottom-up’ population mapping approaches, highlighting innovations in input data, statistical methods, and validation techniques. We examine ongoing challenges, including partial observation of buildings under forest canopies, population displacement detection, and institutional adoption. Finally, we discuss emerging opportunities to enhance these approaches through better integration with traditional data systems, capacity strengthening and co-production with national institutions, often facilitated by UN organisations, such as United Nations Population Fund (UNFPA), and the use of novel data streams to develop more timely, accurate, and useful small area population estimates for planning and humanitarian purposes.
Preprints.Org
Lazar, Attila
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Boo, Gianluca
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Chamberlain, Heather R.
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Nnanatu, Chibuzor Christopher
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Darin, Edith C
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Leasure, Douglas R
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Yankey, Ortis
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Gadiaga, Assane
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Juran, Sabrina
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de la Rúa, Luis
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Espey, Jessica Mary
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Tatem, Andrew J.
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Lazar, Attila
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Boo, Gianluca
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Chamberlain, Heather R.
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Nnanatu, Chibuzor Christopher
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Darin, Edith C
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Leasure, Douglas R
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Yankey, Ortis
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Gadiaga, Assane
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Juran, Sabrina
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de la Rúa, Luis
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Espey, Jessica Mary
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Tatem, Andrew J.
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[Unknown type: UNSPECIFIED]

Record type: UNSPECIFIED

Abstract

Population data at small area scales are essential for effective decision-making, affecting public health, disaster response, and resource allocation, amongst other issues. While national censuses remain the foundational source of population data, they may face challenges such as high cost, infrequency, and coverage gaps, which can hinder timely data availability. Geospatial statistical approaches to address these challenges using limited microcensus surveys have been demonstrated, and the field has advanced substantially in recent years, with significant developments in both data sources and modelling methodologies. New approaches now enable the use of routine health intervention campaign data, improved satellite-derived settlement mapping, and novel Bayesian frameworks to produce high-quality small area population estimates where traditional enumeration is difficult or outdated. Various countries are increasingly applying these techniques to support census operations, health program planning, and humanitarian response. This Perspective reviews recent advances in ‘bottom-up’ population mapping approaches, highlighting innovations in input data, statistical methods, and validation techniques. We examine ongoing challenges, including partial observation of buildings under forest canopies, population displacement detection, and institutional adoption. Finally, we discuss emerging opportunities to enhance these approaches through better integration with traditional data systems, capacity strengthening and co-production with national institutions, often facilitated by UN organisations, such as United Nations Population Fund (UNFPA), and the use of novel data streams to develop more timely, accurate, and useful small area population estimates for planning and humanitarian purposes.

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preprints202506.1625.v1 - Author's Original
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Published date: 19 June 2025

Identifiers

Local EPrints ID: 505854
URI: http://eprints.soton.ac.uk/id/eprint/505854
PURE UUID: e5d85710-c940-4213-9f58-2143c1efb770
ORCID for Attila Lazar: ORCID iD orcid.org/0000-0003-2033-2013
ORCID for Gianluca Boo: ORCID iD orcid.org/0000-0002-4078-8221
ORCID for Heather R. Chamberlain: ORCID iD orcid.org/0000-0003-0828-6974
ORCID for Chibuzor Christopher Nnanatu: ORCID iD orcid.org/0000-0002-5841-3700
ORCID for Edith C Darin: ORCID iD orcid.org/0000-0002-8176-092X
ORCID for Douglas R Leasure: ORCID iD orcid.org/0000-0002-8768-2811
ORCID for Ortis Yankey: ORCID iD orcid.org/0000-0002-0808-884X
ORCID for Jessica Mary Espey: ORCID iD orcid.org/0000-0002-5140-7463
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 21 Oct 2025 16:54
Last modified: 25 Oct 2025 02:20

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Contributors

Author: Attila Lazar ORCID iD
Author: Gianluca Boo ORCID iD
Author: Chibuzor Christopher Nnanatu ORCID iD
Author: Edith C Darin ORCID iD
Author: Douglas R Leasure ORCID iD
Author: Ortis Yankey ORCID iD
Author: Assane Gadiaga
Author: Sabrina Juran
Author: Luis de la Rúa
Author: Jessica Mary Espey ORCID iD
Author: Andrew J. Tatem ORCID iD

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