Evidence map›Paper›PMID 42479703›Full record

ArticlePloS one2026

Spatial distribution and associated factors influencing 2024 Measles-Rubella vaccination campaign coverage among children aged 9-59 months in Mainland Tanzania: A multi-level mixed-effect analysis.

Hajirani M Msuya, Samwel Lwambura, Ibrahim Msuya, Omar Lweno, Bakari Fakih, Mwifadhi Mrisho, Hassan Tearish, Gumi Abdallah, Selemani Mmbaga, August Kuwawenaruwa and 7 more

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Hajirani M MsuyaIfakara Health Institute, Dar es Salaam, Tanzania.ORCID https://orcid.org/0009-0006-5750-261X
Samwel LwamburaIfakara Health Institute, Dar es Salaam, Tanzania.
Ibrahim MsuyaIfakara Health Institute, Dar es Salaam, Tanzania.
Omar LwenoIfakara Health Institute, Dar es Salaam, Tanzania.
Bakari FakihIfakara Health Institute, Dar es Salaam, Tanzania.
Mwifadhi MrishoIfakara Health Institute, Dar es Salaam, Tanzania.
Hassan TearishIfakara Health Institute, Dar es Salaam, Tanzania.
Gumi AbdallahIfakara Health Institute, Dar es Salaam, Tanzania.
Selemani MmbagaIfakara Health Institute, Dar es Salaam, Tanzania.
August KuwawenaruwaIfakara Health Institute, Dar es Salaam, Tanzania.
Moza KassimZanzibar University, Zanzibar, Tanzania.
Kamaria KassimRegency Medical Centre, Paediatrics and Child Health, Dar es Salaam, Tanzania.
Farida HassanIfakara Health Institute, Dar es Salaam, Tanzania.
Joseph MdachiMinistry of Health, Dodoma, Tanzania.
Furaha KyesiMinistry of Health, Dodoma, Tanzania.
William MwengeeWorld Health Organization, Tanzania Country Office, Dar es Salaam, Tanzania.
Abdallah MkopiIfakara Health Institute, Dar es Salaam, Tanzania.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGlobally, 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.

methodsA 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.

resultsThe 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.

conclusionThis 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.

Indexed as

Immunization ProgramsMeaslesMeasles VaccineRubellaRubella VaccineVaccination CoverageChild, PreschoolCross-Sectional StudiesFemaleHumansInfantMaleTanzaniaMeasles VaccineRubella Vaccine

Identifiers

PMID42479703
PMCPMC13387559

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.