<i>Salmonella</i>Typhimurium Infections Associated with Peanut Products
Bibliographic record
Abstract
BACKGROUND: Contaminated food ingredients can affect multiple products, each distributed through various channels and consumed in multiple settings. Beginning in November 2008, we investigated a nationwide outbreak of salmonella infections. METHODS: A case was defined as laboratory-confirmed infection with the outbreak strain of Salmonella Typhimurium occurring between September 1, 2008, and April 20, 2009. We conducted two case-control studies, product "trace-back," and environmental investigations. RESULTS: Among 714 case patients identified in 46 states, 166 (23%) were hospitalized and 9 (1%) died. In study 1, illness was associated with eating any peanut butter (matched odds ratio, 2.5; 95% confidence interval [CI], 1.3 to 5.3), peanut butter-containing products (matched odds ratio, 2.2; 95% CI, 1.1 to 4.7), and frozen chicken products (matched odds ratio, 4.6; 95% CI, 1.7 to 14.7). Investigations of focal clusters and single cases associated with nine institutions identified a single institutional brand of peanut butter (here called brand X) distributed to all facilities. In study 2, illness was associated with eating peanut butter outside the home (matched odds ratio, 3.9; 95% CI, 1.6 to 10.0) and two brands of peanut butter crackers (brand A: matched odds ratio, 17.2; 95% CI, 6.9 to 51.5; brand B: matched odds ratio, 3.6; 95% CI, 1.3 to 9.8). Both cracker brands were made from brand X peanut paste. The outbreak strain was isolated from brand X peanut butter, brand A crackers, and 15 other products. A total of 3918 peanut butter-containing products were recalled between January 10 and April 29, 2009. CONCLUSIONS: Contaminated peanut butter and peanut products caused a nationwide salmonellosis outbreak. Ingredient-driven outbreaks are challenging to detect and may lead to widespread contamination of numerous food products.
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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 | 0.002 |
| 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 | 0.001 |
| 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".