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Record W2067301960 · doi:10.1017/s0950268800004714

Modelling the impact of immunization on the epidemiology of varicella zoster virus

2000· article· en· W2067301960 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEpidemiology and Infection · 2000
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity of ManitobaUniversité Laval
FundersMedical Research Council
KeywordsIncidence (geometry)VaccinationMedicineEpidemiologyTransmission (telecommunications)ImmunizationVaricella zoster virusVaricella vaccineMass vaccinationPediatricsChickenpox VaccineImmunologyVirologyVirusInternal medicineAntibodyComputer scienceMathematics

Abstract

fetched live from OpenAlex

The objective of this study was to develop and apply a dynamic mathematical model of VZV transmission to predict the effect of different vaccination strategies on the age-specific incidence and outcome of infection. To do so a deterministic realistic age-structured model (RAS) was used which takes account of the increased potential for transmission within school aged groups. Various vaccine efficacy scenarios, vaccine coverages and vaccination strategies were investigated and a sensitivity analysis of varicella incidence predictions to important parameters was performed. The model predicts that the overall (natural and breakthrough) incidence and morbidity of varicella would likely be reduced by mass vaccination of 12-month-old children. Furthermore, adding a catch-up campaign in the first year for 1-11 year olds seems to be the most effective strategy to reduce both varicella incidence and morbidity (in the short and long term), though with the possible detrimental effect of increasing the incidence of zoster.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.079
GPT teacher head0.362
Teacher spread0.284 · 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