Investigation of Two Outbreaks of Hepatitis A Virus Infections Linked to Fresh and Frozen Strawberries Imported from Mexico – 2022–2023
Bibliographic record
Abstract
Foodborne hepatitis A illnesses and outbreaks have been associated with the consumption of ready-to-eat foods contaminated with the feces of person(s) shedding hepatitis A virus (HAV). Outbreaks have been linked to fresh and frozen produce imported from countries where HAV is endemic, hygiene and sanitation are inadequate, or food safety standards are lacking or unenforced. In 2022 and 2023, federal, state, and international partners investigated two multijurisdictional outbreaks of infections involving the same HAV genotype IA strain linked to fresh and frozen organic strawberries sourced from a single grower in Baja California, Mexico. These resulted in 39 reported cases in the U.S. and Canada, 21 hospitalizations, and no reported deaths. The United States Food and Drug Administration (FDA), Canadian Food Inspection Agency, and U.S. state partners conducted traceback investigations for fresh strawberries in 2022, while FDA and U.S. state partners traced back frozen strawberries in 2023. Based on the traceback investigations, implicated strawberries were harvested during the 2022 growing season and sold to fresh and frozen berry markets. During a farm inspection in Mexico in 2023, gaps were observed in agricultural practices that could have contributed to the contamination of strawberries with HAV. FDA did not detect HAV in the two frozen strawberry samples linked to the recalled lots or environmental water samples collected at the implicated grower in 2023; no samples were collected during the 2022 investigation. Indicator organisms associated with human fecal contamination (male-specific coliphage and crAssphge) were detected in environmental water. Challenges in these investigations included limited recall of food exposures, exposures associated with multiple purchase dates, commingling of strawberries within the frozen market supply chains, and complexities with communicating these outbreak investigations to the public.
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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 | 0.001 |
| 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".