Comparison of phylogenetic metrics of transmission in symptomatic and asymptomatic tuberculosis
Bibliographic record
Abstract
Summary Background Understanding drivers of Mycobacterium tuberculosis ( Mtb ) transmission remains a critical challenge in high-burden settings. Tuberculosis control efforts traditionally target symptomatic individuals, yet the role of asymptomatic cases in sustaining transmission is increasing recognized. Methods We conducted a genomic and epidemiological analysis of Mtb isolates collected in Mato Grosso do Sul, Brazil, between 2008 and 2024. From 2017 to 2022, active case finding was performed in three of the state’s largest prisons, whereby sputum was collected from individuals irrespective of symptoms and tested by GeneXpert and culture. We evaluated several metrics of recent transmission from symptomatic and asymptomatic individuals, including phylogenetic clustering, Time-scaled Haplotype Density (THD), Local Branching Index (LBI), and transmission probabilities inferred using the Bayesian Reconstruction and Evolutionary Analysis of Transmission Histories (BREATH). Findings We sequenced 2,362 Mtb strains, of which 3.5% (115/2,362) were resistant to at least one drug, and 0.6% (16/2,362) were multi-drug resistant. Most strains were lineage 4, and 78.2% of all isolates were part of a genomic cluster. Among 2,362 individuals with tuberculosis, 1,137 were incarcerated at the time of diagnosis. Among these, 505 were identified through active case finding: 277 had symptomatic disease and 228 had asymptomatic tuberculosis. There was no significant difference in phylogenetic clustering proportion (77% vs. 85%; p= 0.816), THD (median 0.50 vs. 0.39; p = 0.120), or LBI (median 0.00863 vs. 0.00871; p = 0.086) between symptomatic and asymptomatic individuals. Bayesian transmission trees revealed no significant difference in the number of secondary infections inferred from symptomatic compared with asymptomatic individuals (p = 0.56). These findings were consistent across genomic clusters and robust to model assumptions. Interpretation We identified no differences in transmission from symptomatic compared with asymptomatic individuals, using several genomic measures of transmission, underscoring the substantial contribution that asymptomatic tuberculosis makes to transmission at the population level. Evidence before this study We searched PubMed from inception to June 1, 2025, without language restrictions, using the terms “tuberculosis”, “asymptomatic”, “transmission”, “infectiousness” and “genomic epidemiology”. We also reviewed reference lists of relevant studies and reports from the WHO Global Tuberculosis Programme. Most available evidence on the contribution of asymptomatic tuberculosis to transmission comes from cross-sectional contact studies, which typically use tuberculin skin tests or interferon gamma release assays to measure Mycobacterium tuberculosis infection risk in contacts. These studies have generally found no major differences in infection risk between contacts of symptomatic and asymptomatic individuals, but they measure lifetime infection risk and cannot establish the source of exposure. Few studies have used genomic epidemiology to directly assess transmission by symptom status, and those that exist have been small in scale and limited in scope. Mathematical modelling has suggested that asymptomatic individuals could account for a substantial proportion of transmission, but empirical, population-level data from high-incidence settings remain scarce. Added value of this study We combined genomic, epidemiological, and clinical data from over 2,362 M. tuberculosis isolates collected in Mato Grosso do Sul, Brazil, including more than 500 cases identified through active case finding in prisons, to directly compare multiple genomic metrics of transmission between symptomatic and asymptomatic individuals. We found no significant difference in genomic clustering, phylogenetic epidemic success, or the number of estimated secondary infections between groups. Our study is among the largest to date to evaluate transmission resulting in tuberculosis disease by symptom status. These findings provide robust, population-based evidence that asymptomatic tuberculosis can contribute to transmission at levels comparable to symptomatic disease, even in settings with extensive case finding. Implications of all the available evidence Our findings, in combination with previous evidence, indicate that symptom-based case detection strategies are insufficient to substantially reduce tuberculosis transmission. In high-burden settings, systematic screening irrespective of symptoms, is essential to identify and treat infectious cases earlier. Public health programmes should prioritize expanding active case finding in both high-risk institutional settings and the community to capture asymptomatic individuals who may sustain 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".