Economic Evaluation of Human Papillomavirus Vaccination in Developed Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: With promising efficacy results from randomized control trials of human papillomavirus (HPV) vaccines and the availability of new screening paradigms, policymakers are being asked to make recommendations and decisions regarding the optimal strategies to reduce HPV infection and disease. Such decisions are increasingly being made with significant input from mathematical and economic models. The demand for modeling has resulted in the publication of numerous mathematical models looking at the cost-effectiveness of HPV vaccination. OBJECTIVE: To review published models that have been used to evaluate the cost-effectiveness of HPV vaccination in developed countries and highlight points of consensus and disagreement in methods and findings. METHODS: This review consists of cost-effectiveness studies published in the peer-reviewed literature before August 2008. RESULTS: Despite variations in methods, modeling studies are producing consistent conclusions: (1) vaccinating young girls against HPV is likely to be cost- effective; (2) vaccinating boys will most likely not be cost- effective in countries that can reach high coverage rates in girls, and (3) results are most sensitive to the duration of vaccine protection. However, results from analyses examining the effectiveness and cost-effectiveness of vaccinating boys when coverage rates are low (< or = 80%) and catch-up strategies have reached conflicting conclusions.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 it