Spatial Distribution and Associated Factors Influencing 2024 Measles-Rubella Vaccination Campaign Coverage among Children Aged 9-59 Months in Mainland Tanzania

Abstract

Introduction: Globally, measles remains a major cause of child mortality and rubella is the leading cause of birth defects among all infectious diseases. In Mainland Tanzania, eliminating measles and rubella remains challenging due to geographical diversity, uneven healthcare facilities distribution and socio-economic disparities across regions. This study aimed to explore the spatial distribution and associated factors of measles-rubella campaign coverage among children aged 9-59 months in Mainland Tanzania.

Methods: A cross-sectional survey was conducted to assess the spatial distribution and factors influencing Measles-Rubella (MR) vaccination coverage among children aged 9-59 months in mainland Tanzania after the MR campaign implementation in February 2024. The spatial autocorrelation was used to assess vaccination coverage in a study area. Hotspot and cold-spot analysis were performed to describe the spatial cluster of measles-rubella vaccination campaign coverage in Mainland Tanzania based on Getis-Ord Gi* statistics. To identify factors associated with the campaign coverage, we used a multivariable logistic regression model.

Results: The study involved 16,703 children, of whom 81.5% received the MR vaccine during the campaign. Vaccination coverage varied notably between regions, with Tabora and Pwani having a low coverage rate of 58.8% (95% CI: 51.3%-65.9%) and 61.0% (95% CI: 45.0%-75.0%) respectively. The Njombe and Mbeya demonstrating a high coverage rate of 97.4% (95% CI: 90.5%-99.3%) and 95.6% (95% CI: 90.9%-97.9%) respectively. The household wealth quintile and place of residence, caregiver’s education, caregiver’s age and their marital status were associated with receiving MR vaccination during the campaign among children aged 9-59 months in Mainland Tanzania. Spatial distribution revealed significant clustering of vaccination coverage (Moran’s I=0.34, p < 0.01). Hotspot analysis identified eight clusters with low coverage in Tabora (five clusters) and Pwani (three clusters) indicating higher proportions of unvaccinated children. Regions like Njombe and Mbeya were hotspots identified clusters with high vaccination coverage.

Conclusion: This study highlights critical gaps in measles-rubella vaccination coverage in Mainland Tanzania, where regional disparities hinder the achievement of global targets. It stresses the importance of the caregiver’s education and household wealth, advocating for targeted interventions and localized research to address these challenges. To drive progress, integrating Geospatial Artificial Intelligence (GeoAI), spatial data science and satellite technology is crucial. These advanced tools enable real-time, high-resolution mapping, optimizing resource allocation and identifying underserved areas. By leveraging these technologies, we can ensure data-driven, efficient interventions that leave no region behind, ultimately achieving universal vaccination coverage and protecting every child globally.