Achieving tuberculosis elimination in Canada and the USA: giving equal weight to domestic and international efforts
Bibliographic record
Abstract
Abstract A major contributor to the tuberculosis burden in the United States (US) and Canada is the progression of tuberculosis infection acquired before immigration among persons born outside the US and Canada. Domestic interventions against tuberculosis, such as those associated with tuberculosis infection testing and treatment, while critical, are alone insufficient to address tuberculosis and achieve elimination. To hasten tuberculosis elimination in North America, coupling domestic efforts with consistent funding and multifaceted support for tuberculosis detection, treatment, and prevention worldwide is necessary. These efforts will reduce tuberculosis transmission and the prevalence of tuberculosis infection in an increasingly globalized world. We discuss the epidemiologic and economic rationale for this approach, as well as current efforts and potential strategies. We further place in context benchmark tuberculosis programs that have used international funding to achieve a sustained decline in tuberculosis incidence, as exemplars for the importance of such funding to international progress towards elimination. We conclude by providing suggestions for future pathways toward sustainable programs. Following the substantial global and local response to COVID-19, we call for the same intensity to eliminate this millennia-old disease.
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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 | 0.002 | 0.001 |
| 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".