Restaurant-associated foodborne illness outbreaks in the United States: an epidemiological assessment comparing outbreak occurrence and density before [2000–2019] and during [2020] the COVID-19 pandemic
Notice bibliographique
Résumé
Background: Dining experiences and safety protocols at restaurants changed during the COVID-19 pandemic as efforts were made to decrease SARS-CoV-2 transmission. This retrospective observational study evaluated trends in foodborne illness outbreaks associated with restaurant dining prior to and during the COVID-19 pandemic in the United States (US) to assess whether COVID-19-specific risk mitigation strategies may have had a potential effect on foodborne enteric illness outbreaks. Using key concepts learned from the data, this study provides recommendations for hazard control and risk mitigation. Methods: Publicly available data from the Center for Disease Control and Prevention’s National Outbreak Reporting System database were collected on foodborne illness outbreaks associated with restaurant dining from 2000 through 2020. The number of outbreaks and number of cases per outbreak were summarized by year, month, etiology, and suspected exposure setting origin. A Wilcoxon Rank Sum test and a one sample t-test were used to assess for differences in the crude number of restaurant-associated foodborne illness cases and outbreaks (i.e., occurrence) and the number of restaurant-associated foodborne illness cases per outbreak (i.e., density) prior to and during the COVID-19 pandemic, respectively. Results: Approximately 45% of 4,637 foodborne outbreaks were associated with exposure at a restaurant between 2000 and 2020. Overall, there was a 49% decrease in the average number of outbreaks per year in 2020 compared to 2000 through 2019 and a statistically significant decrease in the occurrence of restaurant-associated outbreaks per year in 2020 compared to the 20 years prior was observed (P<0.001). However, there was no statistically significant difference in the density, defined as the number of illnesses per restaurant-associated foodborne illness outbreak, between 2000 and 2019 when compared to 2020 (P=0.439). Conclusions: The findings of this study suggest that increased infection prevention practices specific to COVID-19 may be potentially effective in minimizing the number of enteric illness outbreaks, but they may not be as effective at reducing the density of outbreaks. Establishing multilayered infection control plans that incorporate three well-established frameworks: Hazard Analysis and Critical Control Points (HACCP), the chain of infection, and the National Institute for Occupational Safety and Health hierarchy of controls, may help restaurants more holistically prepare for and respond to future outbreaks or pandemics.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,009 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».