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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.

Original publication

DOI

10.1016/j.vaccine.2018.11.005

Type

Journal article

Journal

Vaccine

Publication Date

18/12/2018

Volume

36

Pages

7965 - 7974

Keywords

Administrative coverage, Methodology, Surveys, Vaccination coverage, Vaccine, Vaccine registry, Child, Preschool, Cohort Studies, Cross-Sectional Studies, Female, Humans, Immunization Programs, Infant, Kenya, Male, Measles Vaccine, Pneumococcal Vaccines, Registries, Regression Analysis, Risk Factors, Time Factors, Vaccination Coverage, Vaccines, Conjugate