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Modelled gridded population estimates for Nigeria 2025 (version 3.0)

Modelled gridded population estimates for Nigeria 2025 (version 3.0)
Modelled gridded population estimates for Nigeria 2025 (version 3.0)
This data release provides gridded population estimates (at spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Nigeria, along with the estimates of the number of people belonging to various age and sex groups. Using robust Bayesian statistical hierarchical modelling framework, population modelling and estimation experts from WorldPop (www.worldpop.org) at the University of Southampton combined ‘head count’ (input population) datasets obtained from the 2022-23 National Malaria Elimination Program (NMEP) with settlement footprint and geospatial covariates to estimate population numbers at high-resolution grid cells. The approach facilitated accounting for the multiple levels of variability within the data, while simultaneously quantifying uncertainties in the parameter estimates. After capturing the spatial variability of population, the modelled estimates were scaled based on the UN WPP July 2025 median national population projections. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 – Phase 2 Scaling project, with funding from the Bill and Melinda Gates Foundation (INV-044979). Project partners included the GRID3 Inc., the Center for Integrated Earth System Information (CIESIN) within the Columbia Climate School at Columbia University, and WorldPop at the University of Southampton. The final statistical modelling was designed, developed, and implemented by Chris Nnanatu supported by Assane Gadiaga. Data processing was done by Assane Gadiaga with additional support from Attila Lazar, Tom Abbott and Heather Chamberlain. Project oversight was done by Attila Lazar and Andy Tatem. The NMEP shared household bednet distribution data along with the location of the households. The settlement footprint data was prepared and shared by CIESIN.
population, Population age and sex structure, Nigeria, gridded population
University of Southampton
Nnanatu, Chris
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Gadiaga, Assane
eada3464-b0a2-4aaa-b594-eff8182c2aee
Abbott, Thomas
6dd117e8-cac5-4862-a3fd-ddbf1cbe94bb
Chamberlain, Heather
cb939de7-ac47-440e-aeb8-a2e36c110785
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Nnanatu, Chris
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Gadiaga, Assane
eada3464-b0a2-4aaa-b594-eff8182c2aee
Abbott, Thomas
6dd117e8-cac5-4862-a3fd-ddbf1cbe94bb
Chamberlain, Heather
cb939de7-ac47-440e-aeb8-a2e36c110785
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Nnanatu, Chris, Gadiaga, Assane, Abbott, Thomas, Chamberlain, Heather, Lazar, Attila and Tatem, Andrew (2025) Modelled gridded population estimates for Nigeria 2025 (version 3.0). University of Southampton doi:10.5258/SOTON/WP00782 [Dataset]

Record type: Dataset

Abstract

This data release provides gridded population estimates (at spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Nigeria, along with the estimates of the number of people belonging to various age and sex groups. Using robust Bayesian statistical hierarchical modelling framework, population modelling and estimation experts from WorldPop (www.worldpop.org) at the University of Southampton combined ‘head count’ (input population) datasets obtained from the 2022-23 National Malaria Elimination Program (NMEP) with settlement footprint and geospatial covariates to estimate population numbers at high-resolution grid cells. The approach facilitated accounting for the multiple levels of variability within the data, while simultaneously quantifying uncertainties in the parameter estimates. After capturing the spatial variability of population, the modelled estimates were scaled based on the UN WPP July 2025 median national population projections. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 – Phase 2 Scaling project, with funding from the Bill and Melinda Gates Foundation (INV-044979). Project partners included the GRID3 Inc., the Center for Integrated Earth System Information (CIESIN) within the Columbia Climate School at Columbia University, and WorldPop at the University of Southampton. The final statistical modelling was designed, developed, and implemented by Chris Nnanatu supported by Assane Gadiaga. Data processing was done by Assane Gadiaga with additional support from Attila Lazar, Tom Abbott and Heather Chamberlain. Project oversight was done by Attila Lazar and Andy Tatem. The NMEP shared household bednet distribution data along with the location of the households. The settlement footprint data was prepared and shared by CIESIN.

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More information

Published date: 29 August 2025
Keywords: population, Population age and sex structure, Nigeria, gridded population

Identifiers

Local EPrints ID: 504248
URI: http://eprints.soton.ac.uk/id/eprint/504248
PURE UUID: 4dbfcb41-2d7a-4f78-8f26-b94f7cbf04c8
ORCID for Chris Nnanatu: ORCID iD orcid.org/0000-0002-5841-3700
ORCID for Heather Chamberlain: ORCID iD orcid.org/0000-0003-0828-6974
ORCID for Attila Lazar: ORCID iD orcid.org/0000-0003-2033-2013
ORCID for Andrew Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 02 Sep 2025 16:45
Last modified: 03 Sep 2025 02:05

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Contributors

Creator: Chris Nnanatu ORCID iD
Creator: Assane Gadiaga
Creator: Thomas Abbott
Creator: Attila Lazar ORCID iD
Creator: Andrew Tatem ORCID iD

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