Associations between litter size and medical treatment of sows during farrowing and lactation

Sow litter sizes have increased recently, and there is a lack of data on the effect of litter size on sow health and sow medical treatment. This study investigated associations between litter size and medical treatment of sows, using data for a 10-year period from one Swedish research farm. The data comprised 1947 litters from 655 Yorkshire sows. Association between litter size and medical treatment of sows during farrowing and lactation investigated using a multivariable multilevel logistic regression model. We found that odds of medical treatment of sows decreased for each additional piglet born up to five piglets (odds ratio 0.50, p = .002). For litter sizes >= 5, the odds for each additional piglet born (odds ratio 1.11, p < .001). Problems with milk let-down in early lactation were the main reason for treatment. Results imply that sows with very small or very large litters may be less profitable

Swedish Trotting Horse Trainers' Perceptions of Animal Welfare Inspections from Public and Private Actors

Simple Summary Harness racing is the most common form of horse racing in Sweden. As public awareness of animal welfare is increasing, the welfare of these horses must be ensured. Trotting horse trainers in Sweden undergo an official animal welfare inspection by the County Administrative Board (CAB) and a private inspection by their own association, the Swedish Trotting Association (STA). This study investigated trainers' perceptions of these different inspections using a digital questionnaire sent out during spring 2021. Of the 396 responding trainers, a majority reported quite positive experiences of both CAB and STA inspections. However, most perceived the STA inspections to be more valuable and the STA inspectors to be more competent than the CAB inspectors. Overall, the competence and manner of the inspector had a stronger association with trainers' perceptions of an inspection than the results of the inspection. While trainers were generally satisfied with the control system, they would like better coordination between the different inspections. In Sweden, the County Administrative Board (CAB) and Swedish Trotting Association (STA) both perform animal welfare inspections of the premises of trotting horse trainers. The CAB inspection checks for compliance with the legislation, and the STA inspection checks for compliance with the private 'Trotter Health Standard', which mainly sets the same requirements as the legislation. This study investigated the views of trainers on these inspections both as separate events and in relation to each other. A digital questionnaire was sent out to trotting horse trainers in Sweden during spring 2021, and 396 trainers responded. Descriptive and statistical analyses were used to evaluate the responses. In general, the trainers reported positive experiences of both the CAB and STA inspections, but they had consistently more positive views about the private STA inspections than the official CAB inspections. The outcome of the inspections, i.e., non-compliance or not, did not affect trainers' perceptions of the inspections, but inspectors' knowledge, manner, and responsiveness had a strong effect. The trainers were generally satisfied with the current control system but would like better coordination between the different inspections

A framework for assessing the confidence in freedom from infection in animal disease control programmes

International audienceIn the Surveillance Tool for Outcome-based Comparison of FREEdom from infection (STOC free) project (https://www.stocfree.eu), a data collection tool was constructed to facilitate standardised collection of input data, and a model was developed to allow a standardised and harmonised comparison of the outputs of different control programmes (CPs) for cattle diseases. The STOC free model can be used to evaluate the probability of freedom from infection for herds in CPs and to determine whether these CPs comply with the European Union’s pre-defined output-based standards. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease for this project because of the diversity in CPs in the six participating countries. Detailed BVDV CP and risk factor information was collected using the data collection tool. For inclusion of the data in the STOC free model, key aspects and default values were quantified. A Bayesian hidden Markov model was deemed appropriate, and a model was developed for BVDV CPs. The model was tested and validated using real BVDV CP data from partner countries, and corresponding computer code was made publicly available. The STOC free model focuses on herd-level data, although that animal-level data can be included after aggregation to herd level. The STOC free model is applicable to diseases that are endemic, given that it needs the presence of some infection to estimate parameters and enable convergence. In countries where infection-free status has been achieved, a scenario tree model could be a better suited tool. Further work is recommended to generalise the STOC free model to other diseases.Dans le cadre du projet européen STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, outil de surveillance permettant de comparer les probabilités d’absence d’infection sur la base des résultats, https://www.stocfree.eu), un outil de recueil des données a été construit pour faciliter une collecte normalisée des données d’entrée ; un modèle a également été élaboré pour permettre une comparaison normalisée et harmonisée des données sur les résultats des différents programmes de contrôle des maladies des bovins. Le modèle STOC free peut être utilisé pour évaluer la probabilité d’absence d’infection au sein des troupeaux dans le cadre des programmes de contrôle et déterminer si ces programmes sont conformes aux normes définies par l’Union européenne en termes de résultats attendus. L’infection par le virus de la diarrhée virale bovine a été choisie comme maladie d'étude pour ce projet en raison de la diversité des programmes de contrôle dans les six pays participants. Les informations relatives aux programmes de contrôle et aux facteurs de risque d’infection ont été recueillies à l’aide de l’outil de collecte des données. Les aspects clés et valeurs par défaut ont été quantifiés en vue d’être inclus dans le modèle STOC free. Un modèle de Markov caché dont les paramètres sont estimés par inférence bayésienne a été considéré comme le plus adapté et développé pour une application aux données issues des programmes de contrôle de la diarrhée virale bovine. Ce modèle a été testé et validé en utilisant des données réelles des programmes de contrôle du virus de la diarrhée virale bovine des pays participants ; le code informatique correspondant a été rendu public. Le modèle STOC free utilise des données au niveau des troupeaux, même si des données au niveau des animaux individuels peuvent être incluses une fois agrégées au niveau du troupeau. Le modèle STOC free s’applique aux maladies endémiques, puisqu’un certain niveau de présence de l’infection est nécessaire pour estimer les paramètres et permettre la convergence. Dans les pays ayant obtenu le statut indemne d’infection, un modèle du type arbre de scénario pourrait être un outil plus adapté. Des travaux supplémentaires sont recommandés pour généraliser le modèle STOC free à d’autres maladie

A framework for assessing confidence in freedom from infection in animal disease control programmes

In the Surveillance Tool for Outcome-based Comparison of FREEdom from infection (STOC free) project (https://www.stocfree.eu), a data collection tool was constructed to facilitate standardised collection of input data, and a model was developed to allow a standardised and harmonised comparison of the outputs of different control programmes (CPs) for cattle diseases. The STOC free model can be used to evaluate the probability of freedom from infection for herds in CPs and to determine whether these CPs comply with the European Union's pre-defined output-based standards. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease for this project because of the diversity in CPs in the six participating countries. Detailed BVDV CP and risk factor information was collected using the data collection tool. For inclusion of the data in the STOC free model, key aspects and default values were quantified. A Bayesian hidden Markov model was deemed appropriate, and a model was developed for BVDV CPs. The model was tested and validated using real BVDV CP data from partner countries, and corresponding computer code was made publicly available. The STOC free model focuses on herd-level data, although that animal-level data can be included after aggregation to herd level. The STOC free model is applicable to diseases that are endemic, given that it needs the presence of some infection to estimate parameters and enable convergence. In countries where infection-free status has been achieved, a scenario tree model could be a better suited tool. Further work is recommended to generalise the STOC free model to other diseases

Assessment of listing and categorisation of animal diseases within the framework of the Animal Health Law (Regulation (EU) No 2016/429): bluetongue

Non peer reviewe