Assessing the global risk of typhoid outbreaks caused by extensively drug resistant Salmonella Typhi
Bibliographic record
Abstract
Since its emergence in 2016, extensively drug resistant (XDR) Salmonella enterica serovar Typhi (S. Typhi) has become the dominant cause of typhoid fever in Pakistan. The establishment of sustained XDR S. Typhi transmission in other countries represents a major public health threat. We show that the annual volume of air travel from Pakistan strongly discriminates between countries that have and have not imported XDR S. Typhi in the past, and identify a significant association between air travel volume and the rate of between-country movement of the H58 haplotype of S. Typhi from fitted phylogeographic models. Applying these insights, we analyze flight itinerary data cross-referenced with model-based estimates of typhoid fever incidence to identify the countries at highest risk of importation and sustained onward transmission of XDR S. Typhi. Future outbreaks of XDR typhoid are most likely to occur in countries that can support efficient local S. Typhi transmission and have strong travel links to regions with ongoing XDR typhoid outbreaks (currently Pakistan). Public health activities to track and mitigate the spread of XDR S. Typhi should be prioritized in these countries.
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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 | 0.003 |
| 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 | 0.001 |
| 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".