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Introduction: Identifying actionable targets is crucial to improve overall and equity in vaccination coverage, and in line with the global Immunization Agenda 2030. Therefore, this study seeks to assess the prevalence of missed opportunities for simultaneous vaccination (MOSVs) and their impact on vaccination coverage and urban-rural inequity in The Gambia.

Methods: We used data of children aged 12-23 months from The Gambia 2019/2020 demographic and health survey (weighted n = 1355) with seen vaccination cards. We analyzed: the frequency of MOSVs; percentage point coverage reduction attributable to MOSVs for 18 vaccine doses and full basic vaccination; and MOSVs' contribution to urban-rural coverage inequity through Blinder-Oaxaca decomposition.

Results: Sixty percent of children experienced MOSVs, in both urban and rural areas, but urban MOSVs were more seldom corrected (35.9 % vs 45.3 %). All eighteen vaccine doses assessed could have achieved between one to eleven percentage points higher coverage if MOSVs had been avoided, with full basic vaccination gaining even more. While MOSV correction did not impact overall urban-rural coverage inequity, it did exacerbate (explained coefficient = -0.1007; P = 0.002) inequities among children who experienced MOSVs, explaining 95 % of the observed difference.

Conclusion: Our study highlights the prevalence and negative impact of MOSVs on overall vaccination coverage. Although MOSVs did not contribute significantly to the total urban-rural inequity in coverage, they have detrimental effects on vaccination coverage and urban-rural inequity among children who had experienced MOSVs. Addressing MOSVs, can enhance coverage and reduce the risk of under-vaccination, aligning with global initiatives.

Objectives: Six million children were under-vaccinated in 2022. Our study aimed to 1) quantify the magnitude of under-vaccination variation between health facilities, 2) assess to which extent individual and health center level factors contributed to the variation, 3) identify individual and health facility factors associated with under-vaccination, and 4), explore rural vs. urban health facility variations.

Methods: We used data from 61,839 children from The Gambia national routine vaccination register. We cross tabulated under-vaccination status across study variables and fitted two-level random intercept multilevel logistic regression models to measure variance, contribution to the variance, and factors associated with the variance and under-vaccination.

Results: We found that 7% of the prevalence of under-vaccination was due to variation between health facilities. Thirty-seven percent of the variation was explained by individual and health center variables. The variables explained 36% of the variance in urban and 19% in rural areas. Children who were not vaccinated at 4 months or with delayed history, due for vaccination in the rainy season, and health facilities with very small or large population to health worker ratios had higher under-vaccination odds.

Conclusion: Our study indicates that one of the pathways to improving vaccination coverage is addressing factors driving under-vaccination inequities between health facilities through urban-rural differentiated strategies.

Introduction: The Hepatitis B virus that can cause liver cancer is highly prevalent in the Gambia, with one in ten babies at risk of infection from their mothers. Timely hepatitis B birth dose administration to protect babies is very low in The Gambia. Our study assessed whether 1) a timeliness monitoring intervention resulted in hepatitis B birth dose timeliness improvements overall, and 2) the intervention impacted differentially among health facilities with different pre-intervention performances.

Methods: We used a controlled interrupted time series design including 16 intervention health facilities and 13 matched controls monitored from February 2019 to December 2020. The intervention comprised a monthly hepatitis B timeliness performance indicator sent to health workers via SMS and subsequent performance plotting on a chart. Analysis was done on the total sample and stratified by pre-intervention performance trend.

Results: Overall, birth dose timeliness improved in the intervention compared to control health facilities. This intervention impact was, however, dependent on pre-intervention health facility performance, with large impact among poorly performing facilities, and with uncertain moderate and weak impacts among moderately and strongly performing facilities, respectively.

Conclusion: The implementation of a novel hepatitis B vaccination timeliness monitoring system in health facilities led to overall improvements in both immediate timeliness rate and trend, and was especially helpful in poorly performing health facilities. These findings highlight the overall effectiveness of the intervention in a low-income setting, and also its usefulness to aid facilities in greatest need of improvement.

Objective: To assess whether the implementation of a results-based financing (RBF) project in The Gambia resulted in (1) improved national vaccination coverage (2) higher coverage in intervention than non-intervention areas, and (3) improvement in rural–urban coverage inequality.

Methods: The study used a difference-in-differences design, based on repeated cross-sectional data from The Gambian Demographic and Health Surveys 2013 (N = 1650) and 2020 (N = 1456). Full vaccination (receipt of one BCG, 3 OPV, 3 DTP, and 1 measles-containing vaccine doses) and rural–urban vaccination inequality were our outcome variables. The intervention, RBF, was implemented in 5 of the 7 health regions. Covariates controlled for included child’s sex, child’s birth order number, socioeconomic status, ethnicity, distance from health facility, maternal education, mother’s age group, mother’s marital status, and mother’s work status. Poisson regression with robust variance was used to estimate whether coverage changed, and difference-in-differences and difference-in-differences-in-differences were used to ‘assess differences in vaccination coverage change and change in inequalities, respectively.

Results: Total crude full vaccination coverage in The Gambia was 76% in 2013 and 84.6% in 2020. Overall vaccination significantly increased by 16% (95% CI: 9% to 24%) in 2020 compared to 2013, but with a smaller increase in intervention relative to non-intervention areas [PRR 0.88 (CI: 0.78–0.99)]. Rural-urban inequality in vaccination coverage decreased more – by 13% [0.87 (0.78–0.98)] – in RBF than non-RBF regions.

Conclusion: Vaccination coverage improved over the study period though we have no evidence to ascribe the coverage gains to the RBF intervention. However, our study suggests that the RBF project has contributed to reducing rural–urban inequalities in the regions it was implemented.