Tuberculosis in the Inuit Community of Quebec, Canada
Bibliographic record
Abstract
In low-incidence countries targeting tuberculosis (TB) elimination, TB remains a problem of a few high-risk groups. In Canada, Aboriginals, and particularly the Arctic Inuit communities, have witnessed dramatic decreases in TB during the 1960s to 1970s, but rates remain at least 10 to 20 times higher than the national average. We are describing the results of an integrated traditional and molecular epidemiology study of all culture-positive Mycobacterium tuberculosis cases in the Arctic Inuit communities of Quebec from 1990 until 2000. The demographic characteristics of the 46 TB cases included in the study were most notable for a bimodal age distribution (48% under 25 years). Genotyping analysis using multiple modalities (IS6110 restriction fragment length polymorphism, spoligotype, mycobacterial interspersed repetitive units-variable number tandem repeats) showed that 76% (35/46) of TB cases were clustered (six clusters, median size four cases) and estimated that at least 62.5% of TB cases were due to ongoing transmission. By integrating the epidemiologic and genotyping data, we observed that the genotyping clustering results were concordant with recognized epidemiologic links but most notably identified previously unrecognized intervillage transmission. This study demonstrates significant ongoing transmission in a geographically isolated, low-density population. In a resource-rich country such as Canada, these communities illustrate some of the persistent challenges of TB control and elimination.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".