Human Papillomavirus Vaccine Uptake and Effectiveness Among Gay, Bisexual, and Other Men Who Have Sex with Men
Bibliographic record
Abstract
Gay, bisexual, and other men who have sex with men (GBM) have a high burden of human papillomavirus (HPV)-associated diseases and thus are prioritized for HPV vaccination. Since 2015/16, the Canadian provinces of British Columbia, Ontario, and Quebec have offered publicly funded HPV vaccination for GBM aged ≤26 years. This manuscript-based dissertation evaluated the uptake and effectiveness of HPV vaccine in GBM soon after these targeted HPV immunization programs were implemented. The Engage Cohort Study is a prospective cohort of 2,449 sexually active GBM aged ≥16 years in Vancouver, Toronto, and Montreal, Canada. Participants were recruited using respondent-driven sampling from 2017 to 2019 and followed for 12 months. At each visit, participants self-reported their HPV vaccination history and, for a subset of younger GBM aged 16-30 years, self-collected anal specimens for HPV DNA testing. HPV-positive specimens were genotyped using the Roche Linear Array® commercial assay. Despite these targeted HPV immunization programs, anal HPV infection was highly prevalent among young, sexually active GBM, with over one-quarter infected with ≥1 vaccine-preventable type at baseline. HPV vaccination (self-reported receipt of ≥1 dose) was associated with lower anal HPV prevalence, incidence, and persistence of vaccine-preventable types, independent of sexual risk behaviours and after correcting for non-differential exposure misclassification associated with self-reported HPV vaccination. Vaccine effectiveness was higher when vaccination was initiated at younger ages or soon after sexual debut, consistent with current immunization guidelines that recommend vaccination prior to HPV exposure to maximize benefit. HPV vaccine coverage increased among Canadian GBM over the 12-month study period, with larger gains among younger GBM who were eligible for the publicly funded programs. Despite the high uptake among younger GBM (60-73% across cities), estimates remained below the national target of 90%, suggesting that many GBM remain at risk for HPV and its associated diseases. Community-based strategies are needed to improve HPV vaccine access and uptake through the GBM-targeted immunization programs, alongside our school-based universal programs. These findings will inform best practices for HPV primary prevention in GBM.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".