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Mapping the Timeliness of Routine Childhood Vaccination in the Gambia: A Spatial Modelling Study.

Vaccine(2023)

Cited 0|Views23
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Abstract
Introduction: Timeliness of routine vaccination shapes childhood infection risk and thus is an important public health metric. Estimates of indicators of the timeliness of vaccination are usually produced at the national or regional level, which may conceal epidemiologically relevant local heterogeneities and make it difficult to identify pockets of vulnerabilities that could benefit from targeted interventions. Here, we demonstrate the utility of geospatial modelling techniques in generating high-resolution maps of the prevalence of delayed childhood vaccination in The Gambia. To guide local immunisation policy and prioritize key interventions, we also identified the districts with a combination of high estimated prevalence and a significant population of affected infants.Methods: We used the birth dose of the hepatitis-B vaccine (HepB0), third-dose of the pentavalent vaccine (PENTA3), and the first dose of measles-containing vaccine (MCV1) as examples to map delayed vaccination nationally at a resolution of 1 x 1-km2 pixel. We utilized cluster-level childhood vaccination data from The Gambia 2019-20 Demographic and Health Survey. We adopted a fully Bayesian geostatistical model incorporating publicly available geospatial covariates to aid predictive accuracy. The model was implemented using the integrated nested Laplace approximation-stochastic partial differential equation (INLA-SPDE) approach.Results: We found significant subnational heterogeneity in delayed HepB0, PENTA3 and MCV1 vaccinations. Specific districts in the central and eastern regions of The Gambia consistently exhibited the highest prevalence of delayed vaccination, while the coastal districts showed a lower prevalence for all three vaccines. We also found that districts in the eastern, central, as well as in coastal parts of The Gambia had a combination of high estimated prevalence of delayed HepB0, PENTA3 and MCV1 and a significant population of affected infants. Conclusions: Our approach provides decision-makers with a valuable tool to better understand local patterns of untimely childhood vaccination and identify districts where strengthening vaccine delivery systems could have the greatest impact.
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