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Record W2129070212 · doi:10.1186/1471-2458-7-236

Prioritization strategies for pandemic influenza vaccine in 27 countries of the European Union and the Global Health Security Action Group: a review

2007· review· en· W2129070212 on OpenAlexfundno aff
Masja Straetemans, Udo Buchholz, Sabine Reiter, Walter Haas, Gérard Krause

Bibliographic record

VenueBMC Public Health · 2007
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersRijksinstituut voor Volksgezondheid en MilieuSocialstyrelsenInstitut de Veille SanitaireEuropean Centre for Disease Prevention and ControlBundesministerium für Gesundheit und FrauenRobert Koch InstitutKoch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyBundesministerium für GesundheitPublic Health AgencyPublic Health Agency of Canada
KeywordsPandemicMedicineEuropean unionAction planPublic healthEnvironmental healthInfluenza vaccineEconomic growthVirologyVaccinationBusinessDiseaseCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)NursingInternational trade

Abstract

fetched live from OpenAlex

BACKGROUND: Although there is rapid progress in vaccine research regarding influenza pandemic vaccines it is expected that pandemic influenza vaccine production can only start once the pandemic virus has been recognized. Therefore, pandemic vaccine capacity will be limited at least during the first phase of an influenza pandemic, requiring vaccine prioritization strategies. WHO recommends developing preliminary priorities for pandemic vaccine use. The goal of this review is to provide a thorough overview of pandemic vaccine prioritization concepts in the 27 European Union (EU) member states and the four non-EU countries of the Global Health Security Action Group. METHODS: Between September and December 2006 data was collected for each country through two data sources: (i) the national influenza pandemic plan; (ii) contacting key persons involved in pandemic planning by email and/or phone and/or fax. RESULTS: Twenty-six (84%) countries had established at least one vaccine priority group. Most common reported vaccine priority groups were health care workers (HCW) (100%), essential service providers (ESP) (92%) and high risk individuals (HRI) (92%). Ranking of at least one vaccine priority group was done by 17 (65%) of 26 countries. Fifteen (88%) of these 17 countries including a ranking strategy, decided that HCW with close contact to influenza patients should be vaccinated first; in most countries followed and/or ranked equally by ESP and subsequently HRI. Rationales for prioritization were provided by 22 (85%) of 26 countries that established vaccine priority groups. There was large variation in the phrasing and level of detailed specification of rationales. Seven (32%) of 22 countries providing rationales clearly associated each vaccine priority group with the specific rationale. Ten (32% of the 31 countries studied) countries have consulted and involved ethical experts to guide decisions related to vaccine prioritization. CONCLUSION: In the majority of the countries the establishment of vaccine priority groups, ranking and underlying rationales are in line with WHO recommendations. In most public plans the criteria by which prioritized groups are identified are not easily recognizable. Clarity however, may be necessary to assure public acceptability of the prioritization. Ethical experts, results of modelling exercises could play an increasing role in the future decision making process.

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)0.026
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.946
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.252
GPT teacher head0.515
Teacher spread0.263 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2007
Admission routes1
Has abstractyes

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