Modelled gridded population estimates for Kongo-Central 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 m grid cells) for Kongo-Central Province in the Democratic Republic of Congo (DRC), along with estimates of the number of people belonging to various age-sex groups. 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 Democratic Republic of the Congo for 2023, settlement footprints 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. This time period corresponds to the PDRS survey date for Kongo-Central. 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, 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 Ortis Yankey. 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 8.0) (CIESIN, 2025).

本数据集发布提供了刚果民主共和国（Democratic Republic of the Congo, DRC）中央刚果省的网格化人口估算数据，空间分辨率为3弧秒（约100米网格单元），同时包含不同年龄-性别分组的人口数量估算结果。项目团队依托2023年刚果民主共和国抗疟疾行动中，由国家疟疾控制规划（National Malaria Control Programme, PNLP）收集的分发前登记调查（Pre-Distribution Registration Survey, PDRS）数据、居民点覆盖范围数据与地理空间协变量，采用贝叶斯统计分层建模框架，在网格单元层面完成人口数量的建模与估算。该方法可同时兼顾数据内的多层级变异性，还能量化参数估算的不确定性。此类基于模型的人口估算可视为最精准匹配2023年的人口数据，该时间节点与中央刚果省的PDRS调查时间完全一致。尽管本方法具备足够鲁棒性，可明确抵消数据集中的主要随机偏差，但需注意：观测数据收集过程中随机误差之外的来源所引发的系统性偏差，大概率仍会存在。

本数据集由南安普敦大学世界人口研究组（WorldPop Research Group）制作。本工作属于GRID3第二阶段扩展项目（GRID3 – Phase 2 Scaling project），由盖茨基金会（Gates Foundation, INV-044979）资助。项目合作伙伴包括GRID3、哥伦比亚大学哥伦比亚气候学院下属的综合地球系统信息中心（Center for Integrated Earth System Information, CIESIN），以及南安普敦大学的WorldPop团队。最终的统计建模由Ortis Yankey设计、开发并实施，数据处理工作由Ortis Yankey完成，Heather Chamberlain提供了额外支持。项目监督由Chris Nnanatu、Attila Lazar与Andy Tatem负责。经杀虫剂处理蚊帐（insecticide treated net, ITN）分发活动的PDRS数据由PNLP及其执行合作伙伴收集、处理、匿名化并共享。居民点范围数据由CIESIN（2024）编制并共享。本数据集已裁剪至GRID3-CIESIN医疗区域范围（8.0版本，CIESIN, 2025）。