Manufacturing costs of HPV vaccines for developing countries
Bibliographic record
Abstract
BACKGROUND: Nearly all of the 500,000 new cases of cervical cancer and 270,000 deaths occur in middle or lower income countries. Yet the two most prevalent HPV vaccines are unaffordable to most. Even prices to Gavi, the Vaccine Alliance, are unaffordable to graduating countries, once they lose Gavi subsidies. Merck and Glaxosmithkline (GSK) claim their prices to Gavi equal their manufacturing costs; but these costs remain undisclosed. We undertook this investigation to estimate those costs. METHODS: Searches in published and commercial literature for information about the manufacturing of these vaccines. Interviews with experts in vaccine manufacturing. FINDINGS: This detailed sensitivity analysis, based on the best available evidence, finds that after a first set of batches for affluent markets, manufacturing costs of Gardasil for developing countries range between $0.48 and $0.59 a dose, a fraction of its alleged costs of $4.50. Because volume of Cervarix is low, its per unit costs are much higher, though at comparable volumes, its costs would be similar. INTERPRETATION: Given the recovery of fixed and annual costs from sales in affluent markets, Merck's break-even price to Gavi could be $0.50-$0.60, not $4.50. These savings could support Gavi programs to strengthen delivery and increase coverage. Outside Gavi, prices to lower- and middle-income countries, with profit, could also be lowered and made available to millions more adolescents at risk. These estimates and their policy implications deserve further discussion.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".