Automatic early detection of induced colic in horses using accelerometer devices.

BACKGROUND: To seek appropriate veterinary attention for horses with colic, owners must recognise early signs. Direct observation of horse behaviour has several drawbacks: it is time-consuming, hard to see subtle and common behavioural signs, and is based on intuition and subjective decisions. Due to recent advances in wearables and artificial intelligence, it may be possible to develop diagnostic software that can automatically detect colic signs. OBJECTIVES: To develop a software algorithm to aid in the detection of colic signs and levels of pain. STUDY DESIGN: In vivo experiments. METHODS: Transient colic was induced in eight experimental mares with luteolytic doses of prostaglandin. Veterinarians observed the horses before and throughout the interventions and assigned pain scores which were used to separate colic episodes into none (pain score ≤5), level 1 (pain score 6-10) or level 2 (pain score ≥11). Accelerometric data and videos were collected throughout the experiments and using accelerometric data, the horse's behaviour was classified into normal and 10 pain-related behaviours and an activity index was calculated. Models were designed that utilised behaviour and activity index characteristics both detecting the presence of colic and assessing its severity. To determine the accuracy of the model, the ground truth, that is the veterinarians' observation of colic signs and assessment of pain level, was compared with the automatic detection system. RESULTS: The cross-validation analysis demonstrated an accuracy of 91.2% for detecting colic and an accuracy of 93.8% in differentiating between level 1 colic and level 2 colic. The model was able to accurately classify 10 pain-related behaviours and distinguish them from normal behaviour with a high accuracy. MAIN LIMITATIONS: We included a limited number of horses with severe pain related behaviours in the dataset. This constraint affects the accuracy of categorising colic severity rather than limiting the algorithms' capacity to identify early colic signs. CONCLUSIONS: Our system for early detection of colic in horses is unique and innovative, and it can distinguish between colic of varying severity.

Horse Jumping and Dressage Training Activity Detection Using Accelerometer Data.

Equine training activity detection will help to track and enhance the performance and fitness level of riders and their horses. Currently, the equestrian world is eager for a simple solution that goes beyond detecting basic gaits, yet current technologies fall short on the level of user friendliness and detection of main horse training activities. To this end, we collected leg accelerometer data of 14 well-trained horses during jumping and dressage trainings. For the first time, 6 jumping training and 25 advanced horse dressage activities are classified using specifically developed models based on a neural network. A jumping training could be classified with a high accuracy of 100 %, while a dressage training could be classified with an accuracy of 96.29%. Assigning the dressage movements to 11, 6 or 4 superclasses results in higher accuracies of 98.87%, 99.10% and 100%, respectively. Furthermore, during dressage training, the side of movement could be identified with an accuracy of 97.08%. In addition, a velocity estimation model was developed based on the measured velocities of seven horses performing the collected, working, and extended gaits during a dressage training. For the walk, trot, and canter paces, the velocities could be estimated accurately with a low root mean square error of 0.07 m/s, 0.14 m/s, and 0.42 m/s, respectively.

Cattle farmers' perception of biosecurity measures and the main predictors of behaviour change: The first European-wide pilot study.

The importance of biosecurity as a strategy to prevent and control infectious diseases has increased substantially over the last few decades. Several studies have reported a low implementation level of biosecurity measures (BSM), particularly in cattle farms. In addition, a recent study demonstrated that cattle farmers are well aware of the recommended BSM and recognize them as more effective (in terms of time and costs) than treatment for disease. Therefore, other factors must be considered when it comes to understanding the decision-making process followed by a farmer regarding the adoption of BSM. This study analysed the possible influence of five mental constructs described in the health belief model (HBM) on the adoption of BSM and assessed the possible association of these constructs with different demographic and socio-psychological factors. Through an online survey, 988 questionnaires were completed by cattle farmers originating from Belgium, France, Germany, Spain and the Netherlands. The study revealed that the actual implementation of the BSM seems to be significantly influenced by the farmers' perception of the measures' benefits and the perception of health responsibility. Both constructs are influenced by the farmers' personality in terms of risk aversion and biosecurity knowledge. It was also found that organic farmers had a significantly lower perception of the BSM benefits and of their responsibility towards animal, public and environmental health when compared with other types of farmer. Organic farmers in this study seemed less likely to implement biosecurity measures. To increase the adoption of BSM by cattle farmers, it is therefore important to emphasise the actual evidence-based benefits of the measures and to investigate further how to strengthen cattle farmers' sense of responsibility towards animal, public and environmental health.

A risk-based scoring system to quantify biosecurity in cattle production.

Farm biosecurity includes all measures preventing pathogens from entering (external) and spreading within a herd (internal) and is important in facilitating the shift from cure to prevention in veterinary medicine. To assess biosecurity on farm level quantitatively an objective measurement process is required. This study describes the development and implementation of risk-based weighted biosecurity evaluation tools for veal, beef and dairy cattle farms. Based on risk factors and biosecurity measures associated with priority cattle diseases and the results of a cross-sectional survey on Belgian farms, questions were selected for the Biocheck-tool. The scoring system consists of three separate questionnaires that contain 69 (veal), 104 (beef) and 124 (dairy) questions. Experts in various fields of veterinary medicine were asked to weigh the different biosecurity categories and questions according to the method of Gore. The system obtained provides biosecurity scores per category (external and internal biosecurity) and subcategory (e.g. purchase, transport, health management). The Biocheck tool was subsequently used in a survey to assess biosecurity in 20 veal, 50 beef and 50 dairy farms. For all production systems, both internal and external biosecurity were considered low, resulting in low mean total biosecurity scores of 39.7 points for veal (SD = 7.4), 44.3 for beef (SD = 8.4), and 48.6 points for dairy farms (SD = 8.1), out of a maximum of 100 points. For all farm types, the scores for internal biosecurity were lower compared to external biosecurity. Veal farms scored significantly lower for "purchase" than beef and dairy, while scoring higher for the other subcategories of external biosecurity. In dairy and beef, "purchase and reproduction" was the highest scoring subcategory. For internal biosecurity, "health management" was particularly low in the three farm types, while subcategories exceeding 50 points were rare. With this tool, implementation of biosecurity on cattle farms can be assessed in a standardized and reproducible manner. This evaluation allows for benchmarking of farms and herd-specific advice for improvements.

Biosecurity practices in Belgian veal calf farming: Level of implementation, attitudes, strengths, weaknesses and constraints.

The shift from cure toward prevention in veterinary medicine involves the implementation of biosecurity. In cattle farming, the application of biosecurity measures has been described to a limited degree, yet no data on biosecurity on veal farms is available. A high degree of commingling of veal calves from multiple farms causes frequent disease outbreaks, and thereby high antimicrobial usage and increased risk of antimicrobial resistance. Therefore, this study aimed to describe the current implementation of biosecurity on veal farms in Belgium. To this extent, a list of the most important calf diseases (n = 34) was created, and risk factors and related biosecurity measures for these diseases were determined and included in a questionnaire. Herd visits and face-to-face interviews were conducted on 20 randomly selected veal farms, comprising 8.3% of the target population. A categorical principal component and clustering analysis were performed to determine the influence of the veal companies on the farms' biosecurity level. Awareness of biosecurity was very low among the farmers. All farms used an "all-in, all-out" production system with calves originating from multiple farms without quarantine. On average, farms were filled in 11.4 days (range 2-52). The degree of commingling for these farms was 1.24, meaning that, on average, 124 calves originated from 100 farms. Veterinarians wore farm-specific boots on eight farms (40%) and farm-specific clothes on six farms (30%), while technical advisors wore farm-specific boots on six farms (30%) and farm-specific clothes on four farms (20%). Disinfection footbaths were only used in five farms (25%) despite being present in all farms in the sample. Concerning internal biosecurity, none of the farmers isolated sick animals; only one farmer (5%) had a physically separated hospital pen, and only 11 farmers (55%) both cleaned and disinfected the stables after each production cycle. In most farms, animals were of comparable age. Healthy calves generally remained in the same compartment during the entire production cycle, limiting the risks associated with the movement of animals. No influence of the integrations on the biosecurity level could be determined. It can be concluded that a few biosecurity measures, such as "'all-in, all-out" and compartmentation, are implemented relatively well, while other measures, such as good cleaning and disinfection and proper entrance measures for visitors and personnel can easily be improved. The improvement of measures regarding the introduction of animals of different origins will require more fundamental changes in the veal industry.

Classification of adult cattle infectious diseases: A first step towards prioritization of biosecurity measures.

An emphasis on biosecurity in the cattle industry was made over the years to improve animal and public health. Nevertheless, the level of implementation of biosecurity measures (BSM) remains largely insufficient due to certain constraints. It is therefore necessary to prioritize the different BSM to be applied in accordance with the individual context and the main infectious diseases affecting cattle. Previous prioritization exercises of infectious diseases were neither specific to Belgium nor based on an exhaustive list of diseases. This study aimed at classifying the most important infectious diseases affecting cattle in Belgium. A list of 74 cattle infectious diseases reported in Europe was compiled based on a literature review. Through an online survey, Belgian rural veterinary practitioners (RVP) were asked to assign a score to each disease according to their frequency (question 1), their trends estimated between 2013-15 (question 2), and finally to list the five most important diseases for adult cattle (question 3). Respectively, 107 and 93 RVP answered the first two questions and the last one. Results of the survey were used to classify the diseases based on their frequency, trends, and importance through an additional weighting system and a subsequent regression tree analysis. Belgian laboratory databases and previous disease prioritization exercises were also analysed and taken into account as additional data sources. For the most important diseases identified (those ranked as important by the three data sources), a literature review was performed in PubMed to identify their related risk factors and BSM. A total of 48 infectious diseases were classified as important in Belgium with six of them considered as important from the three data sources: bovine respiratory diseases (BRD), bovine respiratory syncytial virus (BRSV), bovine viral diarrhoea (BVD), infectious bovine rhinotracheitis (IBR), Q fever, and salmonellosis. Their related BSM should be prioritized in terms of BSM implementation.

The effect of a commercial competitive exclusion product on the selection of enrofloxacin resistance in commensal E. coli in broilers.

The effect of a competitive exclusion product (Aviguard®) on the selection of fluoroquinolone resistance in poultry was assessed in vivo in the absence or presence of fluoroquinolone treatment. Two experiments using a controlled seeder-sentinel animal model (2 seeders: 4 sentinels per group) with one-day-old chicks were used. For both experiments, as soon as the chicks were hatched, the birds of two groups were administered Aviguard® and two groups were left untreated. Three days later, all groups were inoculated with an enrofloxacin-susceptible commensal E. coli strain. Five days after hatching, two birds per group were inoculated with either a bacteriologically fit or a bacteriologically non-fit enrofloxacin-resistant commensal E. coli strain. In experiment 2, all groups were orally treated for three consecutive days (days 8-10) with enrofloxacin. Throughout the experiments, faecal excretion of all inoculated E. coli strains was determined on days 2, 5, 8, 11, 18 and 23 by selective plating (via spiral plater). Linear mixed models were used to assess the effect of Aviguard® on the selection of fluoroquinolone resistance. The use of Aviguard® (P < 0.01) reduced the excretion of enrofloxacin-resistant E. coli when no enrofloxacin treatment was administered. However, this beneficial effect disappeared (P = 0.37) when the birds were treated with enrofloxacin. Similarly, bacterial fitness of the enrofloxacin-resistant E. coli strain used for inoculation had an effect (P < 0.01) on the selection of enrofloxacin resistance when no treatment was administered, whereas this effect was no longer present when enrofloxacin was administered (P = 0.70). Thus, enrofloxacin treatment cancelled the beneficial effects from administrating Aviguard® in one-day-old broiler chicks and resulted in an enrofloxacin-resistant flora. RESEARCH HIGHLIGHTS The effect of Aviguard® on the selection of enrofloxacin resistance was assessed in vivo. Without enrofloxacin, Aviguard® reduced the selection of enrofloxacin resistance. When enrofloxacin was administered, it cancelled the beneficial effect of Aviguard®.