Transmission of <i>Mycobacterium tuberculosis</i> in four prisons in Colombia
Bibliographic record
Abstract
Abstract Our study aimed to describe the transmission dynamics and genotypic diversity of Mycobacterium tuberculosis in people deprived of liberty (PDL) in four Colombian prisons. Our cohort study included 64 PDL with bacteriologically confirmed pulmonary tuberculosis diagnosed in four Colombian prisons. The 132 isolates were genotyped using 24-mycobacterial interspersed repeated units-variable number tandem repeats (MIRUs-VNTR). A cluster was defined when ≥2 isolates from different PDL had the same genotype. Tuberculosis acquired in prison was considered when ≥2 persons were within the same cluster and had an epidemiological link. We mapped the place of residence before incarceration and within prisons. We assessed overcrowding and ventilation conditions in the prison that had clusters. We found that the most frequent genotypes were LAM (56.8%) and Haarlem (36.4%), and 45.3% of the PDL diagnosed with tuberculosis were clustered. Most PDL diagnosed in prison came from neighborhoods in Medellin with a high TB incidence. M. tuberculosis infection acquired in prison was detected in 19% of PDL, 9.4% had mixed infection, 3.1% reinfection, and 1.6% relapse. Clusters only appeared in one prison, in cell blocks with overcrowding >100%, and inadequate ventilation conditions. Prisons require the implementation of effective respiratory infection control measures to prevent M. tuberculosis transmission.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".