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Population-level impact of switching to 1-dose human papillomavirus vaccination in high-income countries: examining uncertainties using mathematical modeling

2024· article· en· W4404283627 on OpenAlexafffund
Marc Brisson, Jean‐François Laprise, Mélanie Drolet, Éléonore Chamberland, Élodie Bénard, Emily A. Burger, Mark Jit, Jane J. Kim, Lauri E. Markowitz, Chantal Sauvageau, Stephen Sy

Bibliographic record

VenueJNCI Monographs · 2024
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsInstitut National de Santé Publique du QuébecUniversité LavalCentre hospitalier de l'Université Laval
FundersCenters for Disease Control and PreventionAlliance de recherche numérique du CanadaWestern Canada Research GridBill and Melinda Gates Foundation
KeywordsVaccinationCervical cancerMedicineVaccine efficacyPopulationDemographyHPV infectionHuman papillomavirusDuration (music)CancerImmunologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: A concern in high-income countries is that switching to 1-dose human papillomavirus (HPV) vaccination could cause a rebound in HPV infection and cervical cancer if 1-dose efficacy or duration were inferior to 2 doses. Using mathematical modeling and up-to-date trial-based data, we projected the population-level effectiveness of switching from 2-dose to 1-dose vaccination under different vaccine efficacy and duration assumptions in high-income countries. METHODS: We used HPV-ADVISE (Agent-based Dynamic model for VaccInation and Screening Evaluation), a transmission-dynamic model of HPV infection and cervical cancer, varying key model assumptions to identify those with the greatest impact on projections of HPV-16 and cervical cancer incidence over time: 1) 1-dose vaccine efficacy and vaccine duration, 2) mechanisms of vaccine efficacy and duration over time, 3) midadult (>30 years of age) sexual behavior, 4) progression to cervical cancer among midadults, and 5) vaccination coverage and programs. RESULTS: In high-income countries, 1-dose vaccination would cause no appreciable rebound in HPV-16 infection, except for a limited rebound under the most pessimistic assumptions of vaccine duration (average, 25 years), because 1) the switch would occur when HPV prevalence is low because of high 2-dose vaccination coverage and 2) individuals would be protected during their peak ages of sexual activity (<35 to 40 years of age). Our model projects a more limited rebound in cervical cancer because of a shift to older age at infection, resulting in fewer life-years left to potentially develop cancer. Projections were robust when varying key model assumptions. CONCLUSIONS: High protection during peak ages of sexual activity in high-income countries would likely mitigate any potential rebounds in HPV infection and cervical cancer under the most pessimistic assumptions of 1-dose efficacy and duration.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.109
GPT teacher head0.423
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes2
Has abstractyes

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