Characteristics of Studies Focusing on Vaccine Series Completion Among Children Aged 12–23 Months in Sub-Saharan Africa: A Scoping Review
Bibliographic record
Abstract
Vaccine preventable diseases remain the leading causes of death among children in Sub-Saharan Africa. BACKGROUND/OBJECTIVES: As vaccines provide the best possible protection only when all required doses are received, it is essential to understand how the published literature is designed and conducted regarding the completion of recommended childhood vaccine series for children aged 12-23 months in SSA. METHODS: A comprehensive search was conducted across five databases (PubMed, Embase, CINAHL, Web of Science, and Google Scholar) to identify the relevant literature published between January 2000 through December 2023. RESULTS: = 23, 43.4%). The prevalence and associated factors of vaccination series completion were the most commonly explored topics in the literature. The most frequently reported factors associated with vaccine series completion included the caregiver's education level, household wealth status, number of children under five in the household, knowledge of immunization, maternal education, place of residence, gender of the household head or decision maker, utilization of antenatal or postnatal care visits, place of delivery, distance to a healthy facility or travel time, and possession of a vaccination card. CONCLUSIONS: This scoping review identified methodological gaps in the published literature, including a lack of publications from many Sub-Saharan Africa countries and insufficient evidence on trends and inequalities in vaccine series completion. Future research on vaccine series completion is recommended to address these gaps.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.019 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".