Epidemiology of genital human papillomavirus infections in sequential male sex partners of young females
Bibliographic record
Abstract
ABSTRACT Objectives Couple-based studies have considered human papillomavirus (HPV) transmission between current heterosexual partners (male↔female). Using data from young women and their sequential male partners in the HPV Infection and Transmission among Couples through Heterosexual activity (HITCH) study, we analysed HPV transmission from upstream sexual partnerships (male 1↔female) to downstream sex partners (→male 2). Methods Among 502 females enrolled in the HITCH study (2005-2011, Montréal, Canada), 42 brought one male sex partner at baseline (male 1) and another during follow-up (male 2). Female genital samples, collected at 6 visits over 24 months, and male genital samples, collected at 2 visits over 4 months, were tested for 36 HPV types ( n =1512 detectable infections). We calculated observed/expected ratios with 95% confidence intervals (CIs) for type-specific HPV concordance between males 1 and 2. Using mixed-effects regression, we estimated odds ratios (ORs) with 95% CIs for male 2 testing positive for the same HPV type as male 1. Results Detection of the same HPV type in males 1 and 2 occurred 2.6 times (CI:1.9-3.5) more often than chance. The OR for male 2 positivity was 4.2 (CI:2.5-7.0). Adjusting for the number of times the linking female tested positive for the same HPV type attenuated the relationship between male 1 and 2 positivity, suggesting mediation. Conclusions High type-specific HPV concordance between males 1 and 2 confirms HPV’s transmissibility in chains of sequential young adult sexual partnerships. HPV positivity in an upstream partnership predicted positivity in a downstream male when the linking female partner was persistently positive.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".