Peer-reviewed article
Coverage and timeliness of vaccination and the validity of routine estimates: Insights from a vaccine registry in Kenya
Ifedayo Adetifa, Boniface Karia, Alex Mutuku, Tahreni Bwanaali, Anne Makumi et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This study used a vaccine registry in Kenya to measure the accuracy of standard vaccination coverage estimates. The researchers found that routine surveys overestimate vaccine coverage and protection by ignoring whether vaccinations were given on time, and by not accounting for deaths among unvaccinated children. When vaccines are delayed, standard surveys can give misleading pictures of how well protected a population is against preventable diseases. The study shows that better measurement methods are needed to accurately track immunisation coverage.
Key points
- Surveys of 12-23 month old children overestimate vaccination coverage by 7-8% for most vaccines and by 24% for measles when timeliness is ignored
- Children born in health facilities had 23-44% higher timely vaccination rates, while those first seen during vaccine stock outs had 20-37% lower timeliness
- Standard surveys and administrative reports underestimate the proportion of fully immunised children by 10-14%
- Survey methods fail to account for survivor bias (deaths among unvaccinated children) and recall bias
- Using vaccination timing alongside coverage gives a more accurate picture of population immunity
Limitations
The study is based on data from one health surveillance system in Kilifi, Kenya, so findings may not represent all of Kenya or other countries with different vaccination programmes and health system contexts. The study does not evaluate interventions to improve coverage, so it cannot tell us which strategies are most effective for addressing the measurement gaps it identifies.
Abstract
BACKGROUND: The benefits of childhood vaccines are critically dependent on vaccination coverage. We used a vaccine registry (as gold standard) in Kenya to quantify errors in routine coverage methods (surveys and administrative reports), to estimate the magnitude of survivor bias, contrast coverage with timeliness and use both measures to estimate population immunity. METHODS: Vaccination records of children in the Kilifi Health and Demographic Surveillance System (KHDSS), Kenya were combined with births, deaths, migration and residence data from 2010 to 17. Using inverse survival curves, we estimated up-to-date and age-appropriate vaccination coverage, calculated mean vaccination coverage in infancy as the area under the inverse survival curves, and estimated the proportion of fully immunised children (FIC). Results were compared with published coverage estimates. Risk factors for vaccination were assessed using Cox regression models. RESULTS: We analysed data for 49,090 infants and 48,025 children aged 12-23 months in 6 birth cohorts and 6 cross-sectional surveys respectively, and found 2nd year of life surveys overestimated coverage by 2% compared to birth cohorts. Compared to mean coverage in infants, static coverage at 12 months was exaggerated by 7-8% for third doses of oral polio, pentavalent (Penta3) and pneumococcal conjugate vaccines, and by 24% for the measles vaccine. Surveys and administrative coverage also underestimated the proportion of the fully immunised child by 10-14%. For BCG, Penta3 and measles, timeliness was 23-44% higher in children born in a health facility but 20-37% lower in those who first attended during vaccine stock outs. CONCLUSIONS: Standard coverage surveys in 12-23 month old children overestimate protection by ignoring timeliness, and survivor and recall biases. Where delayed vaccination is common, up-to-date coverage will give biased estimates of population immunity. Surveys and administrative methods also underestimate FIC prevalence. Better measurement of coverage and more sophisticated analyses are required to control vaccine preventable diseases.