Modelled gridded population estimates for Kinshasa Province in the Democratic Republic of Congo version 4.4.
Modelled gridded population estimates for Kinshasa Province in the Democratic Republic of Congo version 4.4.
This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Kinshasa Province in the Democratic Republic of Congo (DRC). The project 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 between the periods 2021 to 2023, settlement extents and geospatial covariates to model and estimate population numbers at grid cell level 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, are most likely to 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, Assane Gadiaga and Krishnaveni KS. Project oversight was done by Attila Lazar, Chris Nnanatu 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 8.0) (CIESIN, 2025).
Kinshasa, Democratic Republic of Congo, DRC, population, gridded
University of Southampton
Nnanatu, Chris
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Yankey, Ortis
9965d053-8afb-462f-b7fe-b270e21f2ec1
Chamberlain, Heather
cb939de7-ac47-440e-aeb8-a2e36c110785
KS, Krishnaveni
d4546605-d9e5-4255-8638-393609a3dc2a
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Nnanatu, Chris
24be7c1b-a677-4086-91b4-a9d9b1efa5a3
Yankey, Ortis
9965d053-8afb-462f-b7fe-b270e21f2ec1
Chamberlain, Heather
cb939de7-ac47-440e-aeb8-a2e36c110785
KS, Krishnaveni
d4546605-d9e5-4255-8638-393609a3dc2a
Lazar, Attila
d7f835e7-1e3d-4742-b366-af19cf5fc881
Tatem, Andrew
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Nnanatu, Chris, Yankey, Ortis, Chamberlain, Heather, KS, Krishnaveni, Lazar, Attila and Tatem, Andrew
(2025)
Modelled gridded population estimates for Kinshasa Province in the Democratic Republic of Congo version 4.4.
University of Southampton
doi:10.5258/SOTON/WP00861
[Dataset]
Abstract
This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Kinshasa Province in the Democratic Republic of Congo (DRC). The project 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 between the periods 2021 to 2023, settlement extents and geospatial covariates to model and estimate population numbers at grid cell level 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, are most likely to 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, Assane Gadiaga and Krishnaveni KS. Project oversight was done by Attila Lazar, Chris Nnanatu 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 8.0) (CIESIN, 2025).
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More information
Published date: 22 December 2025
Keywords:
Kinshasa, Democratic Republic of Congo, DRC, population, gridded
Identifiers
Local EPrints ID: 508062
URI: http://eprints.soton.ac.uk/id/eprint/508062
PURE UUID: 19601069-2283-4b24-97c5-fb627491677a
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Date deposited: 12 Jan 2026 18:03
Last modified: 13 Jan 2026 03:10
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Contributors
Creator:
Chris Nnanatu
Creator:
Ortis Yankey
Creator:
Krishnaveni KS
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