Notice bibliographique
Résumé
Between March and June 2020, a series of outbreaks of coronavirus (SARS-CoV-2) occurred in meat factories extending from Europe to North America, including those in the USA, Canada, Germany, France, Spain and the UK. Many hundreds of workers were affected in an outbreak at Sioux Falls, South Dakota, USA, and at Tonnies, near Gütersloh, North Rhine-Westphalia, Germany, as well as near High River, Alberta, Canada. In a meat factory in Anglesey, Wales, more than 150 workers were affected. Various reasons have been proposed for the outbreaks, including the crowded working conditions, the cold working environment, workers not wearing masks properly or not at all, and the need for workers to talk loudly over the background noise of machinery. Most experts and commentators seem to be baffled and have spoken about the need for further investigations. While those factors may have been involved there are certain practices within such facilities which, I believe, should also be considered. Common to meat factories is the frequent washing down and brushing of floors and surfaces to maintain hygiene. Those procedures are very effective methods for generating large quantities of droplets and aerosols, especially when high-pressure hosing is employed.1 If the floor or surface is contaminated with coronavirus, perhaps unknowingly, by droplets from one or more infected workers, it is likely that aerosols of infectious particles will be dispersed into the atmosphere and would then pose a considerable risk of airborne virus infection for the workers in that environment. Within a chilled atmosphere workers could be at risk for relatively long periods as the virus will be more stable. The occurrence of a high incidence of infection in meat factories within a short period is, I believe, more likely to be the result of workers being infected from the same source simultaneously rather than by person-to-person transmission. In the latter case, the occurrence of cases would have been more protracted due to the five- to 14-day incubation period, instead of the sharp ‘spikes’ that were seen. This is not to say, of course, that both mechanisms did not occur. There might have been a series of introductions, followed by infection from the contaminated environment, followed by person-to-person transmission. There is a need to provide better protection from airborne virus for workers within meat factories Finally, workers could be screened frequently to reduce the likelihood of those with coronavirus entering the facilities.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».