Contact Investigation and Genotyping to Identify Tuberculosis Transmission to Children
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) in young children is an indicator of ongoing community transmission. We examined contact investigations related to pediatric TB, yield for source case identifications and genotypes for relevant Mycobacterium tuberculosis isolates in a low-incidence setting. METHODS: We reviewed public health data for all patients with TB aged <18 years reported to Montreal authorities during 1996 to 2000. M. tuberculosis isolates from patients of all ages were subjected to IS6110-based genotyping, supplemented by spoligotyping, to compare isolates from children and adults during the same years. RESULTS: Sixty-six patients aged <18 years were diagnosed with active TB from 1996 to 2000. Mean age was 11.1 years (standard deviation 6.7 years). Twenty-five children (38%) were Canadian-born, all with at least one foreign-born parent. Nineteen children were diagnosed after contact investigations of known adult cases; 8 underwent no contact investigation. For the remaining 39 children, a total of 616 contacts were identified. The median number of contacts per child was 9 (interquartile range, 6-10). Four hundred eighty-one contacts (78%) underwent tuberculin testing; 188 (39%) were reactors and 186 (39%) began treatment of latent TB. Investigations uncovered 4 probable source cases, all involving parents or other relatives. M. tuberculosis genotyping for 38 children identified up to 14 additional possible source cases; in only one was a possible epidemiologic link evident from public health records. CONCLUSIONS: Among largely foreign-born children with active TB, contact investigations were extensive and often identified latent tuberculosis infection--but rarely source cases. However, genotyping suggested substantial, previously unrecognized transmission to children despite low overall incidence.
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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 | 0.001 |
| 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) | 0.002 | 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".