Development and implementation of a risk assessment and management program for enzootic bovine leukosis in Atlantic Canada
Notice bibliographique
Résumé
Over the past 30 yr, the prevalence of bovine leukemia virus (BLV) infection has increased in North America, including Atlantic Canada, at both the herd and individual cow levels. This has occurred despite increased awareness of the disease and its deleterious effects and despite implementation of management practices aimed at reducing disease transmission. Our objectives were to identify risk factors associated with the within-herd prevalence of BLV-infected cows by using a risk assessment and management program workbook, as well as to determine the current level of BLV prevalence in the Atlantic Canada region. We hypothesized that previously established risk factors, including management practices associated with calf rearing and fly control, would affect within-herd BLV prevalence. Bulk tank milk (BTM) samples were collected in January and April of 2016 and again during the same months in 2017 and 2018 from all dairy farms shipping milk in the region. Samples were tested with ELISA for levels of anti-BLV antibodies to estimate within-herd prevalence. Regional BLV prevalence at the herd level was 88.39% of dairy herds infected in 2016 and 89.30% in 2018. All dairy farms shipping milk and who had BTM samples collected in 2017 (n = 605) were eligible to participate in the risk assessment and management program questionnaire (RAMP), which was developed and distributed to all bovine veterinarians in Atlantic Canada. One hundred and six RAMP were returned, with representation from all 4 provinces. The RAMP results were combined with the mean BTM ELISA results, and univariable logistic regression followed by multivariable logistic regression was performed to investigate the association between RAMP risk factors and the estimated within-herd BLV prevalence. Factors in the multivariable model significantly associated with the odds of a herd being classified as >25% estimated within-herd prevalence included history of diagnosis of clinical BLV and calves receiving colostrum from cows with unknown BLV status. Differences in within-herd prevalence were not associated with hypodermic needle and injection practices, rectal sleeve practices, or using bulls for natural breeding, based on these 106 dairy farms.
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 | 0,000 |
| 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 | 0,000 | 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) | 0,000 | 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 ».