Modelled gridded population estimates for Kasaï Province in the Democratic Republic of Congo version 4.3

Nnanatu, Chris, Yankey, Ortis, Abbott, Thomas, Chamberlain, Heather, Lazar, Attila and Tatem, Andrew (2025) Modelled gridded population estimates for Kasaï Province in the Democratic Republic of Congo version 4.3. University of Southampton doi:10.5258/SOTON/WP00832 [Dataset]

Abstract

This data release provides gridded population estimates (at a spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Kasaï Province in the Democratic Republic of Congo (DRC), including estimates for various age-sex groups. The project team utilized Pre-Distribution Registration Survey (PDRS) data from the National Malaria Control Programme (PNLP), which were collected during anti-malarial campaigns across the DRC. Due to the absence of recent PDRS data for Kasaï, we used data from the neighboring province of Kwilu to train our model and made grid-level predictions for Kasaï, using geospatial covariates specific to Kasaï. The modelling was done using a Bayesian statistical hierarchical modelling framework. The approach facilitated simultaneous accounting for the multiple levels of variability within the data. It also allowed the quantification of uncertainties in parameter estimates. These model-based population estimates can be considered as most accurately representing the year 2023. Although the methods were robust enough to explicitly account for key random biases within the datasets, it is noted that systematic biases, which may arise from sources other than random errors within the observed data collection process, remain. 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 Gates Foundation (INV-044979). Project partners included 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. Data processing was done by Ortis Yankey with additional support from Heather Chamberlain. Project oversight was done by Chris Nnanatu, Attila Lazar, and Andy Tatem. 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: Chris Nnanatu

Creator: Ortis Yankey

Creator: Heather Chamberlain

Creator: Attila Lazar

Creator: Andrew Tatem

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