Opportunities for tuberculosis elimination in the Canadian Arctic: cost-effectiveness of community-wide screening in a remote Arctic community
Bibliographic record
Abstract
Background: In response to a tuberculosis (TB) outbreak in the remote community of Qikiqtarjuaq Nunavut, Canada, community leaders and the territorial government initiated community-wide screening (CWS) for tuberculosis, an expensive undertaking given the high cost of providing medical services in the Canadian arctic. Our study aim was to assess the cost-effectiveness of the Qikiqtarjuaq CWS. Methods: We developed a hybrid decision analysis and Markov model to replicate the experience and extrapolate CWS outcomes over a 20-year time horizon. Following a hypothetical cohort with patient characteristics reflecting the demographic and testing data available from the CWS, the model compared a one-time CWS intervention with the reference case of 'no community-wide screening'. Findings: CWS resulted in improved health gains through prevention of active tuberculosis cases compared with no CWS. It also resulted in increased costs (measured in Canadian dollars), with a very low estimated incremental cost-effectiveness ratio (ICER) of $25.10 (95% URs: cost savings-$15,874) per additional quality adjusted life year (QALY) gained compared with current standard of care approach (no CWS). Community-wide screening in this context would be considered highly cost-effective in this setting. In probabilistic sensitivity analysis, we found >99% of iterations were cost-effective at a willingness to pay threshold of $50,000/QALY gained. Interpretation: While costly, coordinated and intensive community-wide tuberculosis screening activities are highly cost-effective in remote arctic communities when utilized in an outbreak context. Funding: Government of Nunavut.
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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 | 0.015 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".