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Record W7133005684

Economic Burden of Seasonal Influenza in Canada

2024· dissertation· W7133005684 on OpenAlexaboutno aff
Gary Ka Leung Lam

Bibliographic record

VenueTSpace · 2024
Typedissertation
Language
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersSanofi
KeywordsSeasonal influenzaProductivityEconomic impact analysisEconomic costVaccinationHealth careIndirect costsOutpatient visits
DOInot available

Abstract

fetched live from OpenAlex

This study investigates the substantial annual economic impact of seasonal influenza in Canada, alongside its clinical burden. Despite widespread national recommendations and publicly-funded vaccination programs, adult influenza vaccine coverage remains low at 42%. Using a societal perspective, the study estimates the economic costs attributable to influenza, incorporating direct healthcare expenditures, productivity losses, and the value of premature mortality. Results indicate that annually, influenza results in approximately 4,248 deaths, 2,418 ICU admissions, 13,810 hospitalizations, 187,967 emergency department visits, and 334,608 outpatient physician visits in Canada. Direct healthcare costs amount to $375.9 million annually, while indirect productivity losses reach $581.2 million. The cost of premature mortality due to influenza is estimated at $1.68 billion. Altogether, the average annual economic burden of influenza in Canada totals $2.6 billion CAD. These findings underscore a need for more effective prevention strategies to mitigate both the clinical and economic impacts of influenza.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.065
Threshold uncertainty score0.470

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0030.000
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.045
GPT teacher head0.404
Teacher spread0.359 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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