Human papillomavirus vaccination coverage among young, gay, bisexual, and other men who have sex with men and transgender women — 3 U.S. cities, 2016–2018
Bibliographic record
Abstract
Gay, bisexual, and other men who have sex with men (MSM) and transgender women are disproportionately affected by human papillomavirus (HPV). HPV vaccination is routinely recommended for U.S. adolescents at age 11-12 years, with catch-up vaccination through age 26 years. We assessed HPV vaccination coverage and associated factors among young MSM and transgender women. The Vaccine Impact in Men study enrolled MSM aged 18-26 years from clinics in Seattle, Chicago, and Los Angeles, during February 2016-September 2018. Participants self-reported socio-demographic information and HPV vaccination status. Among 1416 participants, 673 (47.5%) reported ≥1 HPV vaccine dose. Among vaccinated participants, median age at first dose was 19 years and median age at first sex was 17 years; 493 (73.3%) reported that their age at first dose was older than their age at first sex. There were significant differences in HPV vaccination coverage by city (range 33%-62%), age, race/ethnicity, and gender identity. Coverage was highest in Seattle, where younger age was the only factor associated with vaccination. Differences in coverage by city may be due to variation in vaccination practices or enrollment at study sites. Increasing both routine and catch-up vaccination will improve coverage among MSM and transgender women.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".