Clinically Unreported Salmonellosis Outbreak Detected via Comparative Genomic Analysis of Municipal Wastewater <i>Salmonella</i> Isolates
Bibliographic record
Abstract
Underdetection of microbial infectious disease outbreaks in human communities carries enormous health costs and is an ongoing problem in public health monitoring (which relies almost exclusively on data from health clinics). Surveillance of municipal wastewater for community-level monitoring of infectious disease burdens has the potential to fill this information gap, due to its easy access to the mixed community microbiome. In the present study, the genomes of 21 S . Java isolates (collected from municipal wastewater in Honolulu) were analyzed; results showed that the same Salmonella strain that caused a known salmonellosis clinical outbreak in spring 2010 remerged as the most dominant strain in municipal wastewater in spring 2011, indicating a new outbreak that was not detected by health clinics. Our results show that wastewater monitoring holds great promise to inform the field of public health regarding outbreak status within communities.
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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 | 0.001 |
| 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) | 0.001 | 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".