Dispersal of Mycobacterium tuberculosis Driven by Historical European Trade in the South Pacific
Bibliographic record
Abstract
Mycobacterium tuberculosis (Mtb) is a globally distributed bacterial pathogen whose population structure has largely been shaped by the activities of its obligate human host. Oceania was the last major global region to be reached by Europeans and is the last region for which the dispersal and evolution of Mtb remains largely unexplored. Here, we investigated the evolutionary history of the Euro-American L4.4 sublineage and its dispersal to Polynesia. Using a phylodynamics approach and a dataset of 236 global Mtb L4.4 genomes we have traced the origins and dispersal of L4.4 strains to New Zealand. These strains are predominantly found in indigenous Māori and Pacific people and we identify a clade of European, likely French, origin that is prevalent in indigenous populations in both New Zealand and Canada. Molecular dating suggests the expansion of European trade networks in the early 19th century drove the dispersal of this clade to the South Pacific. We also identify historical and social factors within the region that have contributed to the local spread and expansion of these strains, including recent Pacific migrations to New Zealand and the rapid urbanization of Māori in the 20th century. Our results offer new insight into the expansion and dispersal of Mtb in the South Pacific and provide a striking example of the role of historical European migrations in the global dispersal of Mtb.
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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 | 0.001 | 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 | 0.001 |
| 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 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".