Population-level health impact of hypothetical waning 1-dose human papillomavirus vaccination and 2-dose mitigation strategies in a high cervical cancer burden setting
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: We simulated the impact of hypothetical waning scenarios of a 1-dose human papillomavirus (HPV) vaccination paired with switching to 2-dose mitigation strategies guided by empirical vaccine trial reporting timelines. METHODS: Using 2 independent mathematical models fitted to a high-burden setting, we projected the cumulative cervical cancer cases averted over 85 years for alternative HPV vaccination scenarios under 2 program adoption timelines: 1) de novo introduction of a 1-dose HPV vaccination and 2) a switch from an existing 2-dose HPV vaccination program to a 1-dose vaccination. We assumed 80% vaccination coverage with the bivalent vaccine and an average duration of a 1-dose HPV vaccine protection of either 30 or 25 years with 100% efficacy. We varied the eligible age group(s) at program introduction and the 2-dose mitigation (single-age cohort or multi-age cohort). If needed for mitigation, reintroduction of 2-dose vaccination was assumed to occur in 2036 (ie, 30 years after initiation of the Costa Rica Vaccine Trial). RESULTS: Under both vaccine adoption timelines, the models projected that countries could achieve the same level of health benefits by switching to 2 doses in 2036 using a multi-age cohort approach as with initiating a 2-dose or 1-dose vaccination program with no waning. With only a single-age cohort 2-dose mitigation approach, 98%-99% of cases would be prevented compared with the health benefits of 2 doses or a noninferior, durable 1 dose. CONCLUSIONS: Countries hesitant to adopt a 1-dose HPV vaccination program may have opportunities to leverage the benefits and efficiency of a 1-dose schedule while awaiting longer-term reporting from 1-dose durability studies, including Costa Rica Vaccine Trial.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 it