DR Congo
DR Congo Immunisation Data Systems Public Health Report: Need and Coverage, Demographic and Geographic Distribution, Risk Factors, Screening and Diagnosis, Treatment Coverage, Programmes, Gaps and Outlook
DR Congo
Only published figures are shown here, with their year and source. The full report keeps reported cases, survey estimates and modelled estimates apart, and names the data gaps.
Immunisation data systems record who has been vaccinated and where children are missed, guiding outreach. This report covers paper registers, electronic immunisation registries and geospatial data.
The report sets out the scale of need for immunisation data systems in DR Congo: who needs it, how many are reached and the health problems it addresses, using DTP3 Coverage, Measles Second-Dose Coverage, Zero-Dose Children, Vaccine-Preventable Disease Cases and Dropout Between Doses.
Need and coverage are broken down by age (infants under 1 year, children 1–4 years, children 5–14 years, adolescents 15–19 years and adults), gender and income, with a focus on zero-dose children, children in urban slums, children in conflict areas, remote rural communities, pregnant women and older adults.
Findings are compared across states, provinces and districts where data allows, and between urban, rural and informal settlement areas, to show where needs are greatest and where gaps between places are widest.
Main risk factors include distance to health services, conflict and insecurity, vaccine hesitancy and misinformation, poverty and low maternal education, weak supply chains and health worker shortages. Income, education, housing, water and sanitation, and gender and social norms are reviewed as social drivers of health.
The report reviews awareness and uptake of immunisation data systems, and how people in need are found, through vaccination registers and home-based records, disease surveillance, coverage surveys and tracing missed children, by group and by area.
It compares the number of people who need immunisation data systems with the number reached, to show the coverage gap and which groups are missed.
Treatment and prevention covered include electronic registries, geospatial microplanning, coverage surveys and data quality reviews, with how widely each is delivered and how well it is sustained.
Health outcomes covered include outbreaks of vaccine-preventable disease, child deaths, disability from preventable disease and strain on health services, and what is known about the effect of immunisation data systems on them.
The report looks at immunisation clinics and outreach posts, cold chain equipment, vaccinators and community mobilisers and vaccine supply chains, the health workforce, and the physical, financial and distance barriers to care, including how people use public and private services.
It describes what immunisation data systems costs to deliver, who pays for it and the costs that fall on households, including funding from government, donors and NGOs.
Worldwide guidance and funding for immunisation data systems include WHO Immunization Agenda 2030, Gavi, the Vaccine Alliance, UNICEF Supply Division and Global Polio Eradication Initiative. The report reviews national programmes, donor and NGO funding, and what is known about their impact.
Year-wise trends and changes across survey rounds are shown and compared with peer countries, with the data collection year and reporting period stated for each figure.
The report names gaps in screening, diagnosis, treatment and access, the high-risk and underserved communities most affected, and where reliable data is missing.
It looks ahead at future need for immunisation data systems, the resources it will require and the areas most at risk of falling behind.
The report closes with key findings, the population groups to prioritise and recommendations on where to target resources. Figures come from WHO/UNICEF Estimates of National Immunization Coverage (WUENIC), Demographic and Health Surveys (DHS), WHO Vaccine-Preventable Disease Surveillance and National Immunisation Programme Data. Reported cases, survey estimates and modelled estimates are kept apart, and missing figures are named as data gaps.
What doctors and scientists are doing in Immunisation Data Systems Public Health Report right now, from free public sources.
Sources: PubMed (US National Library of Medicine), ClinicalTrials.gov, World Bank. Fetched 12 Nov 2026. Papers and trials are found by search words, so the counts are a guide. Titles only; read each paper at its source.
[1] World Bank Open Data, Health spending per person (US$ per person). Retrieved 14 Nov 2026.
[2] World Bank Open Data, Doctors (per 1,000 people). Retrieved 13 Nov 2026.
[3] World Bank Open Data, People aged 65 and over (% of people). Retrieved 13 Nov 2026.
[4] PubMed, Papers added since 1 January 2021 matching this market. Retrieved 12 Nov 2026.
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