KS, Krishnaveni, Utazi, Edson, Cunningham, Alexander, Chamberlain, Heather, Lazar, Attila and Tatem, Andrew (2025) High-resolution, modelled estimates of vaccination coverage for the Democratic Republic of Congo, including estimates of zero-dose- and under-vaccinated children, version 1.0. University of Southampton doi:10.5258/SOTON/WP00878 [Dataset]
Abstract
This data release provides gridded estimates (at a spatial resolution of 30 arc-seconds, approximately 1 km grid cells) of DTP1-3 and MCV1 vaccination coverage rates and numbers of zero-dose and under-vaccinated children for the Democratic Republic of Congo (DRC). The project team utilized the 2023 Enquête de Couverture Vaccinale (ECV) survey dataset, conducted by the Kinshasa School of Public Health (KSPH), along with settlement extents and geospatial covariates, to model and estimate vaccination coverage rates for children aged 12–23 months (at the time of the survey). Estimates were calculated for each grid cell within a Bayesian statistical 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 coverage 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. The un- and under-vaccinated children estimation combined the new vaccination coverage estimates with existing high-resolution population estimates of children aged under one-year-old. The reference year of the un- and under-vaccinated children estimates is 2024. These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 – DRC-GAVI-EAF project, with funding by the Zero Dose Child Vaccination Project of the Equity Acceleration Fund (EAF) of Gavi, the Vaccine Alliance [grant number: FAE/GRID3/001/2024]. Project partners included United Nations Office for Project Services (UNOPS), 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 and developed by C.E. Utazi and implemented by K.S. Krishnaveni. H.R. Chamberlain led on the geospatial data processing of the survey, with support from A. Cunningham, who led the geospatial covariate processing and map production. Project oversight was provided by Attila Lazar and Heather Chamberlain. The 2023 ECV data were collected, processed, anonymised and shared by the KSPH and its implementing partners. The settlement extent data was prepared and shared by CIESIN (2024).
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