Genomic insights into the 2022–2023 <i>Vibrio cholerae</i> outbreak in Malawi
Bibliographic record
Abstract
Abstract Malawi is experiencing its deadliest Vibrio cholerae ( Vc ) outbreak following devastating cyclones, with >58,000 cases and >1,700 deaths reported between March 2022 and May 2023. Here, we use population genomics to investigate the attributes and origin of the Malawi 2022– 2023 Vc outbreak isolates. Our results demonstrate the predominance of ST69 seventh cholera pandemic El Tor (7PET) strains expressing O1 Ogawa (∼80%) serotype followed by Inaba (∼16%) and typical non-outbreak-associated non-O1/non-ST69 serotypes (∼4%). Phylogenetic reconstruction of the current and historical Vc isolates from Malawi, together with global Vc isolates, suggested the Malawi outbreak strains originated from Asia. The unique antimicrobial resistance and virulence profiles of the 2022–2023 isolates, notably the acquisition of ICE GEN /ICEVchHai1/ICEVchind5 SXT/R391-like integrative conjugative elements and a CTXφ prophage, which caused ctxB3 to ctxB7 genotype shift, support the importation hypothesis. These data suggest that the recent importation of ctxB7 O1 strains, coupled with climatic changes, may explain the magnitude of the cholera outbreak in Malawi.
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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 | 0.000 | 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".