Contamination of Foods by Food Handlers: Experiments on Hepatitis A Virus Transfer to Food and Its Interruption
Bibliographic record
Abstract
Hepatitis A virus (HAV) is an important pathogen which has been responsible for many food-borne outbreaks. HAV-excreting food handlers, especially those with poor hygienic practices, can contaminate the foods which they handle. Consumption of such foods without further processing has been known to result in cases of infectious hepatitis. Since quantitative data on virus transfer during contact of hands with foods is not available, we investigated the transfer of HAV from artificially contaminated fingerpads of adult volunteers to pieces of fresh lettuce. Touching the lettuce with artificially contaminated fingerpads for 10 s at a pressure of 0.2 to 0.4 kg/cm(2) resulted in transfer of 9.2% +/- 0.9% of the infectious virus. The pretreatments tested to interrupt virus transfer from contaminated fingerpads included (i) hard-water rinsing and towel drying, (ii) application of a domestic or commercial topical agent followed by water rinsing and towel drying, and (iii) exposure to a hand gel containing 62% ethanol or 75% liquid ethanol without water rinsing or towel drying. When the fingerpads were treated with the topical agents or alcohol before the lettuce was touched, the amount of infectious virus transferred to lettuce was reduced from 9.2% to between 0.3 and 0.6% (depending on the topical agent used), which was a reduction in virus transfer of up to 30-fold. Surprisingly, no virus transfer to lettuce was detected when the fingerpads were rinsed with water alone before the lettuce was touched. However, additional experiments with water rinsing in which smaller volumes of water were used (1 ml instead of 15 ml) showed that the rate of virus transfer to lettuce was 0.3% +/- 0.1%. The variability in virus transfer rates following water rinsing may indicate that the volume of water at least in part influences virus removal from the fingerpads differently, a possibility which should be investigated further. This study provided novel information concerning the rate of virus transfer to foods and a model for investigating the transfer of viral and other food-borne pathogens from contaminated hands to foods, as well as techniques for interrupting such transfer to improve food safety.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".