Analysis of spatiotemporal patterns of TB transmission in a prison outbreak
Bibliographic record
Abstract
Abstract Background In May 2024, a highly infectious pulmonary tuberculosis (TB) case (smear 3+, cavitary disease) was identified after a 7-week symptomatic period in a century-old Montréal prison wing with natural ventilation, housing ∼200 incarcerated persons and experiencing high resident turnover. The investigation aimed to assess the extent of TB transmission and identify spatial-temporal risk patterns in a correctional setting where environmental factors may amplify airborne spread. Methods 571 individuals (538 incarcerated persons, 33 staff) were identified for screening using Toronto's Contact Screening Parameters Tool. For people in custody and staff, screening included symptom questionnaires and initial plus 8-week post-exposure tuberculin skin tests (TSTs). Those with TST contraindications or positive results were referred to a TB clinic. Outreach to released individuals varied by region (letters, calls, SMS). Results Screening participation reached 91% among staff (n = 33), ∼70% among incarcerated persons (n = 241), but <10% among those released (n = 297). Among contacts from low-incidence countries, TST positivity rose with exposure duration (7% for <10 days, 15% for 10-21 days, 19% for 22-64 days, 21% for ≥65 days). Among first-floor contacts housed with the index case, positivity declined with increasing distance from the index cell (<10m: 42%, 10-30m: 22%, >30m: 15%), while upper floors showed no gradient. Four secondary active TB cases, linked by MIRU-VNTR, were identified between July 2024 and March 2025, and 66 latent TB infection cases. Conclusions Though proximity is a known TB risk factor, few investigations have documented clear distance-based gradients in correctional settings, supporting improving environmental measures such as ventilation in aging facilities. Challenges included invalid or missing contact information for contacts no longer incarcerated, low self-administered symptom screening completion, lack of on-site airborne isolation rooms. Key messages • A single infectious TB case in a correctional setting sparked a major outbreak, leading to 4 secondary active cases and 66 latent infections among 571 identified contacts. • Rare evidence of a distance-based transmission gradient highlights the importance of engineering controls such as ventilation to mitigate airborne disease transmission in high-risk congregate settings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".