Switching from a 2-dose to a 1-dose program of gender-neutral routine vaccination against human papillomavirus in Canada: a mathematical modelling analysis
Bibliographic record
Abstract
BACKGROUND: Worldwide, countries are examining whether to implement 1-dose human papillomavirus (HPV) vaccination instead of using 2 doses. To inform policy, we sought to project the population-level impact and efficiency of switching from 2-dose to 1-dose gender-neutral routine HPV vaccination in Canada. METHODS: We used HPV-ADVISE, an individual-based transmission-dynamic model of HPV infections and diseases, to mathematically model vaccination programs in 2 provinces, Quebec, a province with high HPV vaccination coverage (around 85%), and Ontario, which has lower coverage (around 65%). We examined non-inferior and pessimistic scenarios of the efficacy (vaccine efficacy of 98% or 90%) and average vaccine duration (lifelong, 30 yr, or 25 yr) of 1 dose compared with 2 doses (98% vaccine efficacy, lifelong vaccine duration). Our main outcomes were the relative reduction in HPV-16 (by sex) and cervical cancers, and the number of doses needed to prevent 1 cervical cancer. RESULTS: Our model projected that 1-dose HPV vaccination would avert a similar number of cervical cancers as 2 doses in Canada, under various scenarios. Under the most pessimistic scenario (25-yr vaccine duration), 1-dose vaccination would avert fewer cervical cancers than 2 doses, by about 3 percentage points over 100 years. All 1-dose scenarios were projected to lead to elimination of cervical cancer (< 4 cervical cancers/100 000 female-years) and to be a substantially more efficient use of vaccine doses than a 2-dose scenario (1-dose v. no vaccination = 800-1000 doses needed to prevent 1 cervical cancer; incremental doses for 2-dose v. 1-dose vaccination > 10 000 doses needed to prevent 1 additional cervical cancer). INTERPRETATION: If the average duration of 1-dose protection is longer than 25 years, a 1-dose HPV vaccination program would protect those vaccinated during their peak ages of sexual activity and prevent a similar number of HPV-related cancers as a 2-dose program, while being a more efficient use of vaccine doses.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".