Short communication: Risk factors for sonographically detectable udder edema in overbagged cows at dairy shows.

At dairy cow shows, the appearance of the udder is very important. To show cows at their best, udders are often presented in an overbagged state by extending milking intervals before the show. This practice represents an animal welfare issue because it is associated with behavior changes (e.g., excessive abduction and decreased eating time) and may affect the health of the animal. The aim of the current study was to determine the association between various parameters (e.g., milk yield, days in milk, milking procedures, or administration of nonsteroidal anti-inflammatory drugs, steroids, or diuretics) and the sonographically detectable udder edema score. Data were collected from the show catalogs, by interviewing the exhibitors, by analyzing official veterinary treatment protocols and official milking data, via laboratory analysis of blood samples, and by sonographic examinations of the udders at the show. For sonographically detectable udder edema scoring, 3 scans were taken, 1 on each fore quarter and 1 incorporating both rear quarters at the level of the median suspensory ligament. For grading the scans, a scoring system of 4 grades (score 0 = no edema, 1 = slight edema, 2 = moderate edema, 3 = severe edema) was used. Data from 321 cows of different breeds were collected at 4 highly competitive Swiss dairy shows (shows A-D) between January and September 2017. To determine risk factors for sonographically detectable udder edema, data were analyzed with 2 different logistic regression models. In model 1, the odds ratios were 3.33 (milking intervals of ≥16 h vs. <14 h), 3.84 (show A vs. show C), and 7.39 (dairy breeds vs. dual-purpose breeds). Milking intervals of dairy breeds were significantly higher than those of dual-purpose breeds. In model 2, milking interval was the only significant risk factor with an odds ratio of 9.00 for milking intervals of ≥16 h. Only the milking intervals represented a relevant risk factor in both models; therefore, we concluded that the previously described sonographic udder edema scoring is a useful technique for detecting overbagged udders at dairy shows. Its routine implementation may improve cow welfare at dairy shows.

Elimination of virulent strains (aprV2) of Dichelobacter nodosus from feet of 28 Swiss sheep flocks: A proof of concept study.

Virulent ovine footrot caused by Dichelobacter nodosus is an endemic disease worldwide. It is associated with severe pain, impaired animal welfare and economic losses. The competitive real-time PCR for the differentiation of virulent aprV2 and benign aprB2 strains of Dichelobacter nodosus provides an objective, rapid and sensitive diagnostic tool for footrot surveillance, especially as it enables early detection of subclinical carriers of virulent strains. The aim of this study was to evaluate the feasibility of complete elimination of Dichelobacter nodosus strains carrying the aprV2 gene from sheep flocks. The treatment protocol was based on careful removal of loose and severely overgrown claw horn, weekly stand-in foot baths of the entire flock for 10 min per sheep, using a 10% zinc sulphate disinfectant solution, clinical and PCR follow-up and isolation or culling of non-responders. Dichelobacter nodosus strains carrying the aprV2 gene were successfully eliminated from the feet of the sheep of all 28 flocks (100%) participating in the study within 6-19 weeks of weekly foot bathing. A strong correlation between the length of time for weekly foot bathing to eliminate the virulent strains and the within-flock prevalence of clinical footrot at the beginning was observed (rho, 0.68; P <0.001). A statistically significant correlation was not detected between flock size and the length of time for weekly foot bathing (rho, 0.28; P = 0.14), or the prevalence of clinical footrot at study commencement (rho, -0.04; P = 0.82), respectively. In conclusion, a complete elimination of Dichelobacter nodosus strains carrying the aprV2 gene in sheep flocks was possible with a protocol based on careful trimming, weekly stand-in foot baths, and identification of infection using a specific PCR-test and isolation or culling of non-responders.

Development and validation of a novel pedometer algorithm to quantify extended characteristics of the locomotor behavior of dairy cows.

Behavior is one of the most important indicators for assessing cattle health and well-being. The objective of this study was to develop and validate a novel algorithm to monitor locomotor behavior of loose-housed dairy cows based on the output of the RumiWatch pedometer (ITIN+HOCH GmbH, Fütterungstechnik, Liestal, Switzerland). Data of locomotion were acquired by simultaneous pedometer measurements at a sampling rate of 10 Hz and video recordings for manual observation later. The study consisted of 3 independent experiments. Experiment 1 was carried out to develop and validate the algorithm for lying behavior, experiment 2 for walking and standing behavior, and experiment 3 for stride duration and stride length. The final version was validated, using the raw data, collected from cows not included in the development of the algorithm. Spearman correlation coefficients were calculated between accelerometer variables and respective data derived from the video recordings (gold standard). Dichotomous data were expressed as the proportion of correctly detected events, and the overall difference for continuous data was expressed as the relative measurement error. The proportions for correctly detected events or bouts were 1 for stand ups, lie downs, standing bouts, and lying bouts and 0.99 for walking bouts. The relative measurement error and Spearman correlation coefficient for lying time were 0.09% and 1; for standing time, 4.7% and 0.96; for walking time, 17.12% and 0.96; for number of strides, 6.23% and 0.98; for stride duration, 6.65% and 0.75; and for stride length, 11.92% and 0.81, respectively. The strong to very high correlations of the variables between visual observation and converted pedometer data indicate that the novel RumiWatch algorithm may markedly improve automated livestock management systems for efficient health monitoring of dairy cows.

Use of a modified Delphi panel to identify and weight criteria for prioritization of zoonotic diseases in Switzerland.

Zoonotic diseases have a significant impact on public health globally. To prevent or reduce future zoonotic outbreaks, there is a constant need to invest in research and surveillance programs while updating risk management strategies. However, given the limited resources available, disease prioritization based on the need for their control and surveillance is important. This study was performed to identify and weight disease criteria for the prioritization of zoonotic diseases in Switzerland using a semi-quantitative research method based on expert opinion. Twenty-eight criteria relevant for disease control and surveillance, classified under five domains, were selected following a thorough literature review, and these were evaluated and weighted by seven experts from the Swiss Federal Veterinary Office using a modified Delphi panel. The median scores assigned to each criterion were then used to rank 16 notifiable and/or emerging zoonoses in Switzerland. The experts weighted the majority of the criteria similarly, and the top three criteria were Severity of disease in humans, incidence and prevalence of the disease in humans and treatment in humans. Based on these weightings, the three highest ranked diseases were Avian Influenza, Bovine Spongiform Encephalitis, and Bovine Tuberculosis. Overall, this study provided a preliminary list of criteria relevant for disease prioritization in Switzerland. These were further evaluated in a companion study which involved a quantitative prioritization method and multiple stakeholders.