Modelled gridded population estimates for Sud-Ubangi Province in the Democratic Republic of Congo (2023), version 4.3.

Megheib, Mohamed, Yankey, Ortis, Nnanatu, Chris, Abbott, Thomas, Chamberlain, Heather, Lazar, Attila and Tatem, Andrew (2025) Modelled gridded population estimates for Sud-Ubangi Province in the Democratic Republic of Congo (2023), version 4.3. University of Southampton doi:10.5258/SOTON/WP00793 [Dataset]

Abstract

This data release consists of gridded population estimates at a spatial resolution of approximately 100 m for Sud-Ubangi Province in the Democratic Republic of Congo (DRC) and gridded population counts with model uncertainty measures and breakdowns in 40 age-sex groups at a spatial resolution of approximately 100m. The team used the Pre-Distribution Registration Survey (PDRS) data from the National Malaria Control Programme (PNLP) collected as part of anti-malarial campaigns in the DRC for 2023, settlement footprints, and geospatial covariates to estimate population counts at the grid-cell level in a Bayesian hierarchical modelling framework. The framework accounts for multiple levels of variability within the data and allows to quantify model uncertainty. This accounts for multiple levels of variability within the data and allows to quantify model uncertainty. Although the proposed approach accounts for bias in the input population data, other sources of uncertainty are likely to remain. These population estimates are for the year 2023, aligning with the year of the PDRS surveys in Sud-Ubangi. These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 – Phase 2 Scaling project, with funding from the Bill & Melinda Gates Foundation (INV-044979). Project partners included GRID3, the Center for Integrated Earth System Information (CIESIN) within the Columbia Climate School at Columbia University, and WorldPop at the University of Southampton. Mohamed Megheib designed, developed, and implemented the statistical model with support from Ortis Yankey. Mohamed Megheib and Tom Abbott processed the data with additional support from Heather Chamberlain. Attila Lazar, Chris Nnanatu and Andy Tatem provided project oversight. The PDRS data from the malaria insecticide treated net (ITN) distribution campaigns were collected, processed, anonymised and shared by the PNLP and its implementing partners. The settlement extent data was prepared and shared by CIESIN (2024). The data has been clipped to GRID3-CIESIN health area extent (version 6.0) (CIESIN, 2025).

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Contributors

Creator: Ortis Yankey

Creator: Chris Nnanatu

Creator: Heather Chamberlain

Creator: Attila Lazar

Creator: Andrew Tatem

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