Protecting the Next Generation: What Is the Role of the Duration of Human Papillomavirus Vaccine–Related Immunity?
Bibliographic record
Abstract
BACKGROUND: There is strong evidence that human papillomavirus (HPV) is necessary for the development of cervical cancer. A prophylactic HPV vaccine with high reported efficacy was approved in North America in 2006. METHODS: A mathematical model of HPV transmission dynamics was used to simulate different scenarios of natural disease outcomes and intervention strategies. A sensitivity analysis was performed to compensate for uncertainties surrounding key epidemiological parameters. RESULTS: The expected impact that HPV vaccines have on cervical cancer incidence and HPV prevalence in the province of British Columbia in Canada revealed that, for lifelong vaccine-related protection, an immunization routine targeting younger females (grade 6), combined with a 3-year program for adolescent females (grade 9), is the most effective strategy. If vaccine-related protection continues for <10 years, then the targeting of adolescent females would be more beneficial than the targeting of younger females. The incremental benefit if boys, as well as girls, are vaccinated is small. CONCLUSIONS: Optimization of the design of immunization strategies for treatment of HPV depends substantially on the duration of vaccine-induced immunity. Given the uncertainty in estimating this duration, it may be prudent to assume a value close to the lower limit reported and adjust the program when more-accurate information for the length of vaccine-induced immunity becomes available.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".