A systematic review and meta-analysis of the prevalence of caregiver acceptance of malaria vaccine for under-five children in low-income and middle-income countries (LMICs)
Bibliographic record
Abstract
INTRODUCTION: Malaria is the second leading cause of death in children after diarrheal disease, with low- and middle-income countries (LMICs) accounting for over 9 in 10 incidence and deaths. Widespread acceptance and uptake of the RTS,S vaccine, recently approved by the world health organization (WHO), is projected to significantly reduce malaria incidence and deaths. Therefore, we conducted this systematic review and meta-analysis with the aim to determine the malaria vaccine acceptance rate and the factors associated with acceptance. METHODS: We searched six databases including Google Scholar, PubMed, Cochrane, African Index Medicus, The Regional Office for Africa Library, and WHO Institutional Repository for Information Sharing (IRIS) to identify studies evaluating the malaria vaccine acceptance rate. This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. Studies were included if they were original articles published in the English language in peer-reviewed journals and assessed the prevalence of willingness to accept a free malaria vaccine, and not qualitative. The risk of publication bias was checked using both Beggar's funnel plot and Egger's test, while the I2 statistic was used to assess the heterogeneity of the included studies. Study quality was determined using the Newcastle-Ottawa scale. A meta-analysis was performed using a random effects model to evaluate the pooled prevalence of malaria vaccine acceptance. The protocol for this article was registered prospectively on the International Prospective Register for Systematic Reviews (PROSPERO), with ID number CRD42022334282). RESULTS: Our analysis included 11 studies with a total sample size of 14, 666 participants. The aggregate malaria vaccine acceptance rate was 95.3% (95% CI:93.0%-97.2%). Among the general population, the acceptance rate was 96.3% (95% CI:92.0%-99.0%) and among mothers, it was 94.4% (95% CI:90.8%-97.2%). By country, Nigeria had the highest acceptance rate (97.6%, 95% CI:96.0%-98.8%), followed by Ghana (94.6%, 95% CI:93.8%-95.3%) and Tanzania (92.5%, 95% CI:84.4%-97.8%). Sociodemographic determinants of vaccine acceptance included place of residence, tribe, age, sex, occupation, and religion. Reasons for low acceptance included safety concerns, efficacy profile, vaccine's requirement for multiple injections, and poor level of awareness. CONCLUSION: Future efforts should be focused on identifying factors that may improve the actual uptake of the RTS,S vaccine in malaria-endemic communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".