The potential impact and cost-effectiveness of tobacco reduction strategies for tuberculosis prevention in Canadian Inuit communities
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) remains a significant public health problem in Canadian Inuit communities. In 2016, Canadian Inuit had an incidence rate 35 times the Canadian average. Tobacco use is an important risk factor for TB, and over 60% of Inuit adults smoke. We aimed to estimate changes in TB-related outcomes and costs from reducing tobacco use in Inuit communities. METHODS: Using a transmission model to estimate the initial prevalence of latent TB infection (LTBI), followed by decision analysis modelling, we conducted a cost-effectiveness analysis that compared the current standard of care for management of TB and LTBI without additional tobacco reduction intervention (Status Quo) with (1) increased tobacco taxation, (2) pharmacotherapy and counselling for smoking cessation, (3) pharmacotherapy, counselling plus mass media campaign, and (4) the combination of all these. Projected outcomes included the following: TB cases, TB-related deaths, quality-adjusted life years (QALYs), and health system costs, all over 20 years. RESULTS: The combined strategy was projected to reduce active TB cases by 6.1% (95% uncertainty range 4.9-7.0%) and TB deaths by 10.4% (9.5-11.4%) over 20 years, relative to the status quo. Increased taxation was the only cost-saving strategy. CONCLUSIONS: Currently available strategies to reduce commercial tobacco use will likely have a modest impact on TB-related outcomes in the medium term, but some may be cost saving.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".