An International Outbreak Investigation of Salmonella Enteritidis Infections in the United States and Canada Linked to Peaches – 2020
Bibliographic record
Abstract
During August-October 2020, United States federal, state, and Canadian partners investigated an outbreak of Salmonella Enteritidis infections, in the U.S. and Canada, linked to fresh, whole peaches packed and supplied by a grower and packer with multiple orchards (Farm A). In the U.S., a total of 101 ill people and 28 hospitalizations were reported in 17 states, while in Canada, 57 ill people and 12 hospitalizations were reported in two Canadian provinces. The U.S. traceback investigation included 14 points of service (POS), representing 18 illnesses in eight states. Multiple distributors, packinghouses, and orchards supplied bagged and loose peaches during the timeframe of interest to identified POS, with peaches and packinghouses linked to Farm A being the primary source. Orchards of interest were identified for peach fruit, orchard tree leaf, and soil drag swab sample collection using traceback and geospatial analysis. Geospatial analyses showed that several orchards were in proximity to animal operations. While none of the Salmonella isolates recovered matched the outbreak strain, Salmonella Alachua was recovered from peaches and leaf samples, and Salmonella Montevideo was recovered from orchard tree leaves. Whole genome sequencing indicated that these Salmonella isolates were closely related to historical poultry and cattle isolates. Farm A voluntarily recalled loose peaches sold from June 1 to August 3, 2020, and bagged Brand A conventional and organic peaches sold from June 1 to August 19, 2020. Recalled products were likely distributed to at least 14 different countries. Findings suggest that adjacent animal operations may be a potential contributing factor to Salmonella contamination of peaches, with windborne or fugitive dust as a possible route. The findings from this first reported international outbreak of Salmonella linked to peaches grown in the U.S. highlight the importance of grower awareness of adjacent land use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".