An Outbreak of Norovirus Caused by Consumption of Oysters from Geographically Dispersed Harvest Sites, British Columbia, Canada, 2004
Bibliographic record
Abstract
OBJECTIVES: In January 2004, an increase in gastrointestinal illness following oyster consumption was reported in British Columbia. An investigation was initiated to explore the association between norovirus infection and consumption of British Columbia oysters and to identify the source of oyster contamination. METHODS: The outbreak investigation included active surveillance for human cases, two cohort studies, trace-back of oysters, and laboratory testing of oysters and human stools. RESULTS: Enhanced surveillance identified 26 confirmed and 53 clinical cases over 3 months. Oyster consumption was associated with illness in one cohort and suggestive in the other. Oysters were traced to 14 geographically dispersed harvest sites, 18 suppliers, and 45 points of purchase. Norovirus BCCDC03-028 (genotype I.2) was detected in 50% of human specimens. Experimental methods detected norovirus in 12 oyster samples. Sequencing identified mixed clonal patterns in the oysters with one direct sequence match between an oyster sample and the associated human specimen. CONCLUSIONS: The consumption of raw oysters led to norovirus infection. The source of oyster contamination remained unidentified. The geographical dispersion of implicated harvest sites was unusual. APPLICATIONS: This outbreak is unlike most shellfish outbreaks that can be traced back to a common source and challenges conventional thinking that all oyster-related norovirus outbreaks of are a result of point source contamination.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".