Genomic epidemiology of the cholera outbreak in Yemen reveals the spread of a multi-drug resistance plasmid between diverse lineages of <i>Vibrio cholerae</i>
Bibliographic record
Abstract
Abstract The humanitarian crisis in Yemen led in 2016 to the biggest cholera outbreak documented in modern history, with more than 2.5 million suspected cases to date. In late 2018, epidemiological surveillance showed that V. cholerae isolated from cholera patients had turned multi-drug resistant (MDR). We generated genomes from 260 isolates sampled in Yemen between 2018 and 2019 to identify a possible shift in circulating genotypes. 84% of V. cholerae isolates were serogroup O1 belonging to the seventh pandemic El Tor (7PET) lineage, sublineage T13 – same as in 2016 and 2017 – while the remaining 16% of strains were non-toxigenic and belonged to divergent V. cholerae lineages, likely reflecting sporadic gut colonisation by endemic strains. Phylogenomic analysis reveals a succession of T13 clones, with 2019 dominated by a clone that carried an IncC-type plasmid harbouring an MDR pseudo-compound transposon (PCT). Identical copies of these mobile elements were found independently in several unrelated lineages, suggesting exchange and recombination between endemic and epidemic strains. Treatment of severe cholera patients with macrolides in Yemen from 2016 to early 2019 coincides with the emergence of the plasmid-carrying T13 clone. The unprecedented success of this genotype where an SXT-family integrative and conjugative element (SXT/ICE) and an IncC plasmid coinhabit show the stability of this MDR plasmid in the 7PET background, which may durably reduce options for epidemic cholera case management. We advocate a heightened genomic epidemiology surveillance of cholera to help control the spread of this highly-transmissible, MDR clone.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".