Avoiding mixed messages: HPV vaccines and the ‘cure’ for cervical cancer
Bibliographic record
Abstract
Most vaccination programmes are concerned with reducing the prevalence and incidence of a particular infectious disease, such as TB or smallpox. The human papillomavirus (HPV) vaccine, however, is a vaccine that is designed to prevent the development of cervical cancer by protecting the individual against infection by HPV. This chapter examines the evidence base for the policy of a HPV vaccination programme, and suggests that the way in which this information is communicated to the public is loaded and that, furthermore, it may have serious consequences for the screening programme that could, arguably, be counterproductive. Introduction In the autumn of 2008 the UK government commenced the first wave of HPV vaccinations as part of a national programme aimed at 12- and 13-year-old girls. This is to be supplemented with a programme aimed at 18-year-old women. The instigation of the UK programme follows the lead of other countries – specifically the US and Canada – as part of a campaign to tackle cervical cancer. Since the announcement that the UK's Joint Committee on Vaccination and Immunisations recommended a vaccination programme, there has been extensive media coverage aimed at promoting the vaccine in the UK. While the programme is voluntary, it is being undertaken in secondary schools and there is substantial pressure on parents through media reports, celebrity endorsement and TV advertising to agree to the vaccination of their daughters. It is assumed that there is universal support for the vaccine and programme and it is being promoted as the cure for cervical cancer. However, such an approach mixes a number of key public health issues related to the purpose of the programme, who is being given protection, the interaction between different public health programmes and so on, that place public health practitioners and others involved in health promotion and public health in a difficult position. While the HPV vaccine offers some hope of reducing the levels of cervical cancer, concerns have been expressed about its efficacy and the usefulness of the vaccination programme. This is an issue particularly with regard to long-term effects and side effects, and there is concern over the fact that it only protects against four out of the 200 HPV types. For this reason the vaccine does not confer 100% protection and there is still a need to have a national screening programme, particularly for older women.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".