Modeling the Sexual Transmissibility of Human Papillomavirus Infection using Stochastic Computer Simulation and Empirical Data from a Cohort Study of Young Women in Montreal, Canada
Why this work is in the frame
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Bibliographic record
Abstract
The authors estimated plausible ranges of the probability of human papillomavirus (HPV) transmission per coital act among newly forming couples by using stochastic computer simulation. Comparative empirical data were obtained in 1996-2001 from a cohort study of female university students in Montreal, Canada. Female prevalence and frequency of sexual intercourse and condom use were set equal to those in the cohort. Simulations included 240 combinations of male prevalence, the relative risk for protected versus unprotected sex, and per-act transmission probabilities. Those that produced expected HPV incidence within the 95% confidence interval observed in the cohort were selected. The observed 6-month cumulative incidence following acquisition of a new partner was 17.0% (95% confidence interval: 11.4, 23.0). Expected incidences consistent with those from cohort findings occurred in 54/240 simulations. The range of per-act transmission probabilities was 5-100% (median, 40%). Male HPV prevalence was the same as or greater than that for women in all consistent simulations. Varying condom effectiveness did not produce better-fitting data. This simulation suggests that HPV transmissibility is several-fold higher than that for other viral sexually transmitted infections such as human immunodeficiency virus or herpes simplex virus 2. With high transmissibility, any potential protective effect of condoms would disappear over multiple intercourse acts, underlining the need for an effective HPV vaccine.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it