Genomic attributes of Vibrio cholerae O1 responsible for 2022 massive cholera outbreak in Bangladesh
Bibliographic record
Abstract
Abstract In 2022, one of its worst cholera outbreaks began in Bangladesh and the icddr,b Dhaka hospital treated more than 1300 patients and ca. 42,000 diarrheal cases from March-1 to April-10, 2022 1 . Here, we present genomic attributes of V. cholerae O1 responsible for the 2022 Dhaka outbreak and 960 7th pandemic El Tor (7PET) strains from 88 countries. Results show strains isolated during the Dhaka outbreak cluster with 7PET wave-3 global clade strains, but comprise subclade BD-1.2, for which the most recent common ancestor appears to be that responsible for recent endemic cholera in India. BD-1.2 strains are present in Bangladesh since 2016, but not establishing dominance over BD-2 lineage strains 2 until 2018 and predominantly associated with endemic cholera. In conclusion, the recent shift in lineage and genetic attributes, including serotype switching of BD-1.2 from Ogawa to Inaba, may explain the increasing number of cholera cases in Bangladesh.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".