Do self-rated health and previous vaccine uptake influence the willingness to accept MPOX vaccine during a public health emergency of concern? A cross-sectional study
Bibliographic record
Abstract
Monkeypox (MPOX) was declared a global public health emergency of international concern in July 2022. Vaccinations may be an essential strategy to prevent MPOX infections and reduce their impact on populations, especially among at-risk populations. However, less is known about the factors associated with people's willingness to accept the MPOX vaccine in resource-constrained settings. In this study, we examine the associations between self-rated health, previous vaccine uptake, and people's willingness to accept the MPOX vaccine using cross-sectional data from four major cities in Ghana. The data were analyzed using descriptive and logistic regression techniques. We found that the acceptance of the MPOX vaccine is generally low (approximately 32%) in Ghana. The regression analysis reveals that individuals who did not receive vaccines in the past are much less likely to get the MPOX vaccine (AOR:.28; 95% CI:.62-2.37). The association between self-rated health and vaccine acceptance (AOR: 1.22; 95% CI:.62-2.37) disappeared after we accounted for covariates. Based on these findings, we conclude that vaccine uptake history may be critical to people's uptake of the MPOX vaccine.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".