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Record W3112026972 · doi:10.1016/j.ypmed.2020.106354

From cervical cancer elimination to eradication of vaccine-type human papillomavirus: Feasibility, public health strategies and cost-effectiveness

2020· article· en· W3112026972 on OpenAlexaff
Mark Jit, Kiesha Prem, Élodie Bénard, Marc Brisson

Bibliographic record

VenuePreventive Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversité Laval
FundersPublic Health EnglandNational Institute for Health Research Health Protection Research UnitLondon School of Hygiene and Tropical MedicineNational Institute for Health and Care ResearchBill and Melinda Gates Foundation
KeywordsMedicineCervical cancerHuman papillomavirusVaccinationPublic healthHuman papillomavirus vaccineEnvironmental healthGynecologyCancerImmunologyInternal medicineGardasilNursing

Abstract

fetched live from OpenAlex

The Director-General of the World Health Organization has called for global action towards elimination of cervical cancer as a public health problem. Cervical cancer is caused by human papillomavirus (HPV), an infectious agent with no non-human reservoir. One way to achieve this is through very high levels of vaccine coverage that could enable global eradication of vaccine-type HPV. Using the case study of India, we show that HPV eradication can meet all the Dahlem and Strüngmann criteria for feasibility of eradication. It can be achieved with 90% gender-neutral HPV vaccine coverage together with 95% coverage in high-risk groups such as female sex workers. Such a strategy would likely be cost-effective compared to no vaccination. Although it would be more costly in the short-term than achieving cervical cancer elimination alone, it would save costs in the long-term by removing or at least sharply reducing the need for preventive measures.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.231
GPT teacher head0.479
Teacher spread0.249 · 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 teacher head, not a consensus.

Study designObservational
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

Citations22
Published2020
Admission routes1
Has abstractyes

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