Published in PLOS One on 2026-07-21, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Hajirani M. Msuya, Samwel Lwambura, Ibrahim Msuya, Omar Lweno, Bakari Fakih, Mwifadhi Mrisho, Hassan Tearish, Gumi Abdallah, Selemani Mmbaga, August Kuwawenaruwa, Moza Kassim, Kamaria Kassim, Farida Hassan, Joseph Mdachi, Furaha Kyesi, William Mwengee, Abdallah Mkopi
Source: PLOS One • DOI 10.1371/journal.pone.0330134
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
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. Understanding spatial patterns and associated determinants of vaccination coverage is essential for improving campaign effectiveness. 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.
A cross-sectional survey was conducted following the implementation of the February 2024 measles-rubella (MR) vaccination campaign to assess the spatial distribution and factors influencing MR vaccination coverage among children aged 9–59 months in Mainland Tanzania. Spatial autocorrelation was evaluated using Moran’s I to detect clustering, while Local Indicators of Spatial Association (LISA) was used to identify High-High and Low-Low clusters. Hotspot and cold-spot analyses were performed using Getis–Ord Gi* statistics at the 95% confidence level, consistent with standard epidemiological reporting practices, to identify statistically significant spatial clusters. To identify factors associated with the campaign coverage, we used a multivariable logistic regression model.
The study included 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. Njombe and Mbeya demonstrated high MR vaccination coverage 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). The LISA identified two distinct categories of clusters: High-High Clusters (high-coverage) and Low-Low Clusters (low-coverage). High-High Clusters, which indicate regions with high MR vaccine rates surrounded by similar neighbors, are concentrated in regions such as Njombe and parts of Mbeya, whereas Low-Low Clusters, representing regions with low MR coverage, are found in areas like Tabora, Katavi, Dar es Salaam and Pwani. The Getis-Ord Gi* hotspot analysis shows significant clustering, with high-confidence hotspots in the southern highlands (Njombe and Mbeya) and notable cold spots in western Tanzania (Tabora and Katavi) and parts of eastern Tanzania.
This study demonstrates substantial spatial heterogeneity in measles–rubella vaccination coverage across Mainland Tanzania, with persistent geographic inequities driven by socio-economic and demographic factors. These findings demonstrate how integrating geospatial insights with equity-focused planning can support precision public health planning, enabling targeted interventions to close coverage gaps and accelerate progress toward measles and rubella elimination.
Reading this evidence
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This briefing makes the source accessible within the wider public health desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Hajirani M. Msuya, Samwel Lwambura, Ibrahim Msuya, Omar Lweno, Bakari Fakih, Mwifadhi Mrisho, Hassan Tearish, Gumi Abdallah, Selemani Mmbaga, August Kuwawenaruwa, Moza Kassim, Kamaria Kassim, Farida Hassan, Joseph Mdachi, Furaha Kyesi, William Mwengee, Abdallah Mkopi. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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