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Record W4391888991 · doi:10.1016/j.vaccine.2024.02.041

Impact and cost-effectiveness analyses of vaccination for prevention of respiratory syncytial virus disease among older adults in Ontario: A Canadian Immunization Research Network (CIRN) study

2024· article· en· W4391888991 on OpenAlexafffundabout
Affan Shoukat, Carolyn E. Bawden, Gergely Röst, Jason J. LeBlanc, Alison P. Galvani, Joanne M. Langley, Seyed M. Moghadas

Bibliographic record

VenueVaccine · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsNova Scotia Health AuthorityIzaak Walton Killam Health CentreDalhousie UniversityMcGill UniversityNova Scotia HospitalYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanadian Immunization Research NetworkCanada Foundation for InnovationNotsew Orm Sands FoundationNational Institutes of HealthNational Science Foundation
KeywordsMedicineVaccinationCost effectivenessCost-effectiveness analysisQuality-adjusted life yearEconomic evaluationHealth careDisease burdenImmunizationWillingness to payEnvironmental healthCost–benefit analysisDiseasePediatricsDemographyGerontologyImmunologyPopulationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Two prefusion F protein-based vaccines, Arexvy and Abrysvo, have been approved by Health Canada for protecting older adults against respiratory syncytial virus (RSV)-associated lower respiratory tract disease. We estimated the health benefits and cost-effectiveness of these vaccines under a publicly funded single-dose vaccination program in Ontario that targets residents of long-term care homes (LTCHs). Additionally, we evaluated an extended program that broadens vaccination to include community-dwelling older adults. METHODS: A discrete-event simulation model was parameterised with the burden of RSV disease including outpatient care, hospitalisation, and death among adults aged 60 years or older in Ontario, Canada. Accounting for direct and indirect costs (in 2023 Canadian dollars) associated with RSV-related outcomes, we calculated the net monetary benefit using quality-adjusted life-year (QALY) gained, and determined the range of price-per-dose (PPD) for vaccination programs to be cost-effective from both healthcare and societal perspectives over two RSV seasons. The incremental cost-effectiveness ratio (ICER) was calculated to estimate the additional costs required to gain one QALY. RESULTS: Using a willingness-to-pay of $50,000 per QALY gained, we found that vaccinating 90% of residents in LTCHs with Arexvy would be cost-effective from a societal perspective for a PPD up to $163, producing a mean ICER value of $49,984 (95% CI: $47,539 to $52,704) per QALY gained with a two-year budget impact of $463,468 per 100,000 older adults. The reduction of hospitalizations was estimated at 7.0% compared to the no-vaccination scenario. Extending the program to include community-dwelling older adults with a 74% coverage akin to influenza vaccination, Arexvy remains cost-effective for a PPD up to $139, with a mean ICER value of $49,698 (95% CI: 48,022 to 51,388) per QALY gained and a two-year budget impact of $8.63 million. Compared to the no-vaccination scenario, the extended program resulted in a 57.3% reduction in RSV-related hospitalisations. CONCLUSIONS: Vaccinating residents of LTCHs against RSV disease would be cost-effective depending on PPD; extending the program to community-dwelling older adults would provide substantial health benefits, averting significant direct healthcare costs and productivity losses.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.078
Threshold uncertainty score0.569

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.005
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.116
GPT teacher head0.477
Teacher spread0.361 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations16
Published2024
Admission routes3
Has abstractyes

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