How much do smear-negative patients really contribute to tuberculosis transmissions? Re-examining an old question with new tools
Bibliographic record
Abstract
BACKGROUND: Sputum smear microscopy is a common surrogate for tuberculosis infectiousness. Previous estimates that smear-negative patients contribute 13-20% of transmissions and are, on average, 20 to 25% as infectious as smear-positive cases are understood to be high. Herein, we use an ideal real-world setting, a comprehensive dataset, and new high-resolution techniques to more accurately estimate the true transmission risk of smear-negative cases. METHODS: We treated all adult culture-positive pulmonary TB patients diagnosed in the province of Alberta, Canada from 2003 to 2016 as potential transmitters. The primary data sources were the Alberta TB Registry and the Provincial Laboratory for Public Health. We measured, as primary outcomes, the proportion of transmissions attributable to smear-negative sources and the relative transmission rate. First, we replicated previous studies by using molecular (DNA) fingerprint clustering. Then, using a prospectively collected registry of TB contacts, we defined transmission events as active TB amongst identified contacts who either had a 100% DNA fingerprint match to the source case or a clinical diagnosis. We supplemented our analysis with genome sequencing on temporally and geographically linked DNA fingerprint clusters of cases not identified as contacts. FINDINGS: There were 1176 cases, 563 smear-negative and 613 smear-positive, and 23,131 contacts. Replicating previous studies, the proportion of transmissions attributable to smear-negative source cases was 16% (95% CI, 12-19%) and the relative transmission rate was 0.19 (95% CI, 0.14-0.26). With our combined approach, the proportion of transmission was 8% (95% CI, 3-14%) and the relative transmission rate became 0.10 (95% CI, 0.05-0.19). INTERPRETATION: When we examined the same outcomes as in previous studies but refined transmission ascertainment with the addition of conventional epidemiology and genomics, we found that smear-negative cases were ∼50% less infectious than previously thought. FUNDING: Alberta Innovates Health Solutions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".