Human Papillomavirus Infection and Reinfection in Adult Women: the Role of Sexual Activity and Natural Immunity
Bibliographic record
Abstract
There is a paucity of data on whether or not women can be reinfected with human papillomavirus (HPV) types to which they were exposed to earlier in life and on the role of natural immunity. The observation of HPV infection at older ages may be explained by the reactivation of a latent infection or new exposure from sexual activity. Our objective was to analyze the association between reinfection and sexual activity. We analyzed data from 2,462 women enrolled in the Ludwig-McGill cohort and followed every 4 to 6 months for up to 10 years. We performed HPV typing and viral load measurements via PCR and determined HPV-16 seroreactivity at enrollment. Incidence of infection and reinfection were estimated for individual types. Adjusted relative risks (RR) for the association between infection/reinfection and new sexual partners were calculated using Cox regression. Rates of initial infection and reinfection postclearance were statistically comparable. RRs of initial infection or reinfection were consistently associated with new sexual partners [2.4 (95% confidence intervals; 95% CI, 2.0-3.1) for first infection, 3.7 (1.1-13.8) for reinfection with the same type, and 2.3 (1.5-3.7) for reinfection with a different type]. Reinfection in older women was also associated with new sexual partners (RR, 2.8; 95% CI, 1.4-5.3) as were new infections with HPV-16 among women with serologic evidence of prior HPV-16 exposure (RR, 3.0; 95% CI, 1.6-5.3). Viral loads at initial infection and at reinfection were comparable. HPV infection and reinfection were strongly associated with sexual activity. This study suggests that natural immunity does not play a role in controlling the extent of reinfections.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".