Determining a relationship between licensing status and semi-quantitative risk score for BC dairy processing plants
Notice bibliographique
Résumé

 Background: Following the 2014 Gort’s Gouda Cheese Escherichia coli O157:H7 outbreak which resulted in one death and 28 illnesses, an examination of dairy processing plants (DPP) within British Columbia (BC) was undertaken. The intent of this examination was to efficiently allocate resources to ensure a lower likelihood of future outbreaks occurring in a BC DPP and to improve current knowledge regarding DPP practices. A risk-based approach to assessing inspection activities for DPPs was undertaken. As such, the purpose of the project was to create a semi-quantitative tool to assess inherent risk factors of DPPs, after which it would be used to determine appropriate inspection frequencies for these plants based on their risk scores. Finally, a comparison between provincially licensed and federally registered dairies was conducted in order to examine if there was a difference in risk between the two licensing statuses. Methods: A semi-quantitative approach was used to characterize responses to a survey (Shi, 2014) conducted by the BCCDC between August and December 2014. This survey was sent to all DPPs (n=54) operating in BC. Each survey question related to increasing information on conditions found in DPPs, after which a semi-quantitative assessment approach was used to assign a total risk inherent to each DPP due to the conditions found in the facility. The DPPs were then ranked against each other with respect to their risk scores in order to assess which facility was considered of higher risk. Facilities were grouped by their licensing status, provincially licensed or federally registered, and then compared against one another using a two variable t-test in NCSS 10. Semi-quantitative risk assessment was done using an Excel tool designed specifically for the present study. Results: Complete data was obtained for 85%(n=46) of DPPs, with an equal number of provincial and federal DPPs used in the evaluation. Dairies were ranked against one another with respect to their total risk score. A statistically significant difference (p=0.036) was found when comparing the inherent risk of provincial and federal DPPs, with federally registered dairies showing a lower total inherent risk score. Conclusion: The information obtained from this study provided the BCCDC with a standardized risk-based inspection approach. Ranking of DPPs with respect to their inherent risk also allows inspectors to gain better understanding of present day dairies and their high risk issues. This reassessment allows for the development of more efficient inspection schedules in order to effectively allocate inspection resources and to increase the ability for inspectors to capture and prevent risks which would lead to foodborne illnesses.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».