Impacts of Human Papillomavirus Immunization Programs on Rates of Anogenital Warts in British Columbia, Canada, 2000 to 2017
Bibliographic record
Abstract
BACKGROUND: In 2008, British Columbia (BC) implemented a school-based quadrivalent human papillomavirus (HPV-4) immunization program for girls born in 1994 or later. In 2015, an expanded clinic-based program included men who report sex with men (MSM) born in 1989 or later. To evaluate the impacts of HPV-4 programs on anogenital warts (AGWs), diagnosis rates were measured among women who report sex with men (WSM), men who report sex with women (MSW), and MSM. METHODS: Diagnoses of AGW were ascertained from 16 sexually transmitted infection clinics. Rates were calculated as new AGW diagnoses over person-years (py) at risk and stratified by age group, calendar period, and birth cohort. Adjusted relative rates (aRR) were estimated using multivariable Poisson regression. RESULTS: There were 204,832 clinic visits by 85,158 individuals: 28,366 (33%) WSM, 35,688 (42%) MSW, and 14,534 (17%) MSM. After adjusting for age and period, AGW rates in the 1994-1996 birth cohort decreased by 56% overall (1.21 vs. 2.72 cases/100 py; aRR, 0.44; 95% confidence interval [CI], 0.34-0.59), 65% among WSM (0.97 vs. 2.77 cases/100 py; aRR, 0.35; 95% CI, 0.22-0.57), 58% among MSW (1.60 vs. 3.78 cases/100 py; aRR, 0.42; 95% CI, 0.28-0.65), and 41% among MSM (1.14 vs. 1.19 cases/100 py; aRR, 0.59; 95% CI, 0.38-0.91) versus the 1991-1993 birth cohort. CONCLUSIONS: The HPV-4 programs had significant impacts on lowering AGW rates in BC. The greatest decrease was among WSM eligible for the school-based program, followed by birth cohorts of men who likely have sex with HPV-4 eligible women. The smallest decrease among MSM may reflect the later introduction of the clinic-based program.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".