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Record W2009196287 · doi:10.1586/erv.10.151

Optimizing the acceptability, effectiveness and costs of immunization programs: the Quebec experience

2010· review· en· W2009196287 on OpenAlexaffabout
Philippe De Wals

Bibliographic record

VenueExpert Review of Vaccines · 2010
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsImmunizationMedicineImmunization programMeningococcal vaccineSchedulePublic healthBusinessEnvironmental healthNursingComputer scienceImmunology

Abstract

fetched live from OpenAlex

In Canada, publicly funded immunization programs are a provincial/territorial responsibility. In the province of Quebec, much effort has been devoted to optimize the acceptability, effectiveness and cost-effectiveness of publicly funded immunization programs for children during the last 20 years. The aim of this article is to describe how programs are planned, implemented and evaluated and to identify key factors that contribute to the success of this enterprise. A comprehensive framework was developed for the evaluation of new vaccines and new programs in a societal perspective. It is used by the Quebec Immunization Committee to prepare reports proposing options with their costs and consequences for the public health authority. When a decision is made, the implementation of the new program is carefully planned. Surveys and consultations with stakeholders are systematically conducted to identify potential obstacles. A fraction of the budget is always reserved for program evaluation and monitoring. At the present time, the recommended immunization schedule targets 15 different diseases and only 20 injections are offered up to 15 years of age. Vaccine uptake rate is high and, although a reduced number of doses are recommended for several vaccines, program effectiveness is highly satisfactory, as shown for hepatitis B, meningococcal and pneumococcal diseases.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.905
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
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)0.0000.000

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 head0.037
GPT teacher head0.395
Teacher spread0.358 · 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 designOther design
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

Citations10
Published2010
Admission routes2
Has abstractyes

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