The association of housing density, isolation and tuberculosis in Canadian First Nations communities
Bibliographic record
Abstract
BACKGROUND: First Nations communities in Canada experience disproportionately high levels of overcrowded housing, degree of isolation, and rates of tuberculosis (TB). A study was done to assess the association between housing density, isolation, and the occurrence of TB in First Nations communities. METHODS: Average persons per room (ppr), isolation type, average household income, population, and TB cases (1997-1999) at the community level were entered into a database. Tuberculosis notification rates and 95% CI were calculated for different strata of ppr and isolation. Two multiple logistic regression models were developed to examine the association of ppr, isolation, income, and population with the occurrence of >/=1, or >/=2, TB cases in a community. RESULTS: The rate was 18.9 per 100,000 (95% CI: 13.3-24.6) in communities with an average of 0.4-0.6 ppr, while communities with 1.0-1.2 ppr had a rate of 113.0 per 100,000 (95% CI: 95.4-130.5). An increase of 0.1 ppr in a community was associated with a 40% increase in risk of >/=2 TB cases occurring, while an increase of $10,000 in community household income was associated with 0.25 the risk, and being an isolated community increased risk by 2.5 times. CONCLUSIONS: This study shows a significant association between housing density, isolation, income levels, and TB. Overcrowded housing has the potential to increase exposure of susceptible individuals to infectious TB cases, and isolation from health services may increase the likelihood of TB.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".