WHO initiative to increase global and equitable access to influenza vaccine in the event of a pandemic: Supporting developing country production capacity through technology transfer
Bibliographic record
Abstract
Should a highly pathogenic avian influenza virus, such as the H5N1 virus type currently circulating in birds, become transmissible among humans, an effective vaccine, rapidly available in vast quantities, would be the best tool to prevent high case-fatalities and the breakdown of health and social services. The number of vaccine doses that could be produced on demand has risen sharply over the last few years; however, it is still alarmingly short of the 13 billion doses that would be needed if two doses were required to protect fully the world's population. Most developing countries would be last in the queue to benefit from a pandemic vaccine. The World Health Organization, together with governments, the pharmaceutical industry and other stakeholders, has been implementing the global pandemic influenza action plan to increase vaccine supply since 2006. Building capacity in developing countries to manufacture influenza vaccine is an integral part of this plan, as well as research and development into more efficacious technologies, e.g. those that allow significant dose-sparing. To this end, the influenza vaccine technology transfer initiative was launched in 2007 and, to date, vaccine manufacturers in 11 developing countries have received grants to acquire the capacity to produce inactivated or live attenuated influenza vaccine for their populations. In addition, a centralized 'hub' has been established to facilitate training in the new technologies for scientists and regulators in the countries. This supplement of Vaccine is devoted to showcasing the interim results of the WHO initiative and the impressive progress made by the developing country manufacturers.
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How this classification was reachedexpand
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".