The First Outbreak of <i>Salmonella</i> Enteritidis Infections Linked to Frozen Whole Kernel Corn in Canada, 2021–2022
Bibliographic record
Abstract
An investigation into an outbreak of Salmonella enterica serovar Enteritidis (S. Enteritidis) infections in Canada was initiated in October 2021 after a cluster of cases was identified through whole-genome sequencing. A total of 118 cases were identified in five provinces, related by 0–4 whole-genome multilocus sequence typing allele differences. Cases became ill between September 6, 2021 (symptom onset date) and January 27, 2022 (specimen isolation date). The median age of cases was 30 years (range: 1–89 years), and 64% were female. Five hospitalizations and two deaths were reported. Early in the investigation, a cluster of illnesses was identified that ate at different locations of the same restaurant chain (Restaurant Chain A). Several hypothesis-generating methods were conducted to identify the source, including: case re-interviews, menu review, ingredient analysis, traceback investigations, and sampling of food items. These methods identified multiple fresh produce items as possible hypotheses, but the source of the outbreak was identified when a sample of Brand X Individually Quick Frozen (IQF) Corn from Restaurant Chain A tested positive for the outbreak strain of S. Enteritidis. In total, 87% (75/86) of cases reported exposure to, or potential exposure to, corn. Based on the distribution records, 91% (68/75) of these cases could be linked to the recalled Brand X IQF Corn, and of those, 88% (60/68) consumed food from Restaurant Chain A. This article summarizes the first known outbreak investigation of Salmonella associated with frozen corn in Canada and adds evidence to the potential food safety risks associated with frozen vegetables.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".