Global phylogeography and evolutionary history of Shigella dysenteriae type 1
Bibliographic record
Abstract
Together with plague, smallpox and typhus, epidemics of dysentery have been a major scourge of human populations for centuries(1). A previous genomic study concluded that Shigella dysenteriae type 1 (Sd1), the epidemic dysentery bacillus, emerged and spread worldwide after the First World War, with no clear pattern of transmission(2). This is not consistent with the massive cyclic dysentery epidemics reported in Europe during the eighteenth and nineteenth centuries(1,3,4) and the first isolation of Sd1 in Japan in 1897(5). Here, we report a whole-genome analysis of 331 Sd1 isolates from around the world, collected between 1915 and 2011, providing us with unprecedented insight into the historical spread of this pathogen. We show here that Sd1 has existed since at least the eighteenth century and that it swept the globe at the end of the nineteenth century, diversifying into distinct lineages associated with the First World War, Second World War and various conflicts or natural disasters across Africa, Asia and Central America. We also provide a unique historical perspective on the evolution of antibiotic resistance over a 100-year period, beginning decades before the antibiotic era, and identify a prevalent multiple antibiotic-resistant lineage in South Asia that was transmitted in several waves to Africa, where it caused severe outbreaks of disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".