Case report: Infection with Dicrocoelium dendriticum in a Japanese Chin dog

Dicrocoelium dendriticum is a trematode colonising the bile ducts of herbivores. Coproscopic findings in dogs are usually considered gastrointestinal passages of eggs after ingestion of unheated liver tissue or infected ruminant faeces. Here, a Japanese Chin presented with diarrhoea and weight loss. Eggs comparable to D. dendriticum were detected in faeces and infection was confirmed via PCR and by ruling out differential diagnoses. Egg excretion continued for a period of 10 months. Praziquantel (50 mg/kg body weight [BW]) was administered orally for four consecutive days. Egg excretion 10 days after treatment entailed further treatments with 100 mg/kg BW, again for four days. Faecal samples were negative ten days and four weeks afterwards, diarrhoea resolved, and the dog gained weight. In cases of repeated coproscopic positivity for D. dendriticum, an infection with dogs acting as definitive hosts should be considered. Treatment with praziquantel at a higher dosage may be required

Relationship of body condition and milk parameters during lactation in Simmental cows in Bavaria, Germany

In dairy cows the body condition forms a reflection of the energy reserves of the organism. Health, welfare and productivity of dairy cows are strongly associated with changes in body condition. As lactation puts substantial demands on the metabolism of dairy cows, farm management aims at avoiding either a deficient body condition or a substantial loss of body condition within a short period of time. A body condition higher or lower than recommended (over- and underconditioning in the following) compromises dairy cow productivity. While the body condition of Holstein Friesian cows has been thoroughly explored, few is known about the consequences of deviations from a target body condition for health and productivity of cows from other breeds. This study explores the percentage of over- and underconditioned cows at different days post partum [dpp] and their association with production parameters i.e., milk yield, milk fat and milk protein content of Simmental cows on Bavarian farms, categorized by parity (primi- or multiparous). Our study displays that in Simmental cows, overconditioning is more prevalent than underconditioning. While the middle of lactation (dpp = 100–199) resulted in higher percentage of overconditioning, the dry period (dpp = 299) indicated a higher percentage of underconditioned cows. The dry period and the middle of lactation are therefore the most challenging lactation stages for Simmental cows. We found milk protein content to have the strongest association with over- and underconditioning in Simmental cows. The probability of overconditioning was higher with higher milk protein content for every lactation stage and the probability of underconditioning was lower with higher milk protein content in every lactation stage. This study provides a theoretical basis for potential improvements in stockbreeding, which, if implemented, could improve not only the milk yield of Simmental dairy cows, but also their health and welfare

Factors Associated With Lameness in Tie Stall Housed Dairy Cows in South Germany

Lameness remains a major concern for animal welfare and productivity in modern dairy production. Even though a trend toward loose housing systems exists and the public expects livestock to be kept under conditions where freedom of movement and the expression of natural behavior are ensured, restrictive housing systems continue to be the predominant type of housing in some regions. Factors associated with lameness were evaluated by application of multiple logistic regression modeling on data of 1,006 dairy cows from 56 tie stall farms in Bavaria, South Germany. In this population, approximately every fourth cow was lame (24.44% of scored animals). The mean farm level prevalence of lameness was 23.28%. In total, 22 factors were analyzed regarding their association with lameness. A low Body Condition Score (BCS) (OR 1.54 [95%-CI 1.05-2.25]) as well as increasing parity (OR 1.41 [95%-CI 1.29-1.54]) entailed greater odds of lameness. Moreover, higher milk yield (OR 0.98 [95%-CI 0.96-1.00]) and organic farming (OR 0.48 [95%-0.25-0.92]) appeared to be protectively associated with lameness. Cows with hock injuries (OR 2.57 [95%-CI 1.41-4.67]) or with swellings of the ribs (OR 2.55 [95%-CI 1.53-4.23]) had higher odds of lameness. A similar association was observed for the contamination of the lower legs with distinct plaques of manure (OR 1.88 [95%-CI 1.14-3.10]). As a central aspect of tie stall housing, the length of the stalls was associated with lameness; with stalls of medium [(>158-171 cm) (OR 2.15 [95%-CI 1.29-3.58]) and short (171 cm). These results can help both gaining knowledge on relevant factors associated with lameness as well as approaching the problem of dairy cow lameness in tie stall operations

Random forest classification as a tool in epidemiological modelling: Identification of farm-specific characteristics relevant for the occurrence of Fasciola hepatica on German dairy farms

Fasciola hepatica is an internal parasite of both human and veterinary relevance. In order to control fasciolosis, a multitude of attempts to predict the risk of infection such as risk maps or forecasting models have been developed. These attempts mainly focused on the influence of geo-climatic and meteorological features. Predicting bovine fasciolosis on farm level taking into account farm-specific settings yet remains challenging. In the present study, a new methodology for this purpose, a data-driven machine learning approach using a random forest classification algorithm was applied to a cross-sectional data set of farm characteristics, management regimes, and farmer aspects within two structurally different dairying regions in Germany in order to identify factors relevant for the occurrence of F. hepatica that could predict farm-level bulk tank milk positivity. The resulting models identified farm-specific key aspects in regard to the presence of F. hepatica. In study region North, farm-level production parameters (farm-level milk yield, farm-level milk fat, farm-level milk protein), leg hygiene, body condition (prevalence of overconditioned and underconditioned cows, respectively) and pasture access were identified as features relevant in regard to farm-level F. hepatica positivity. In study region South, pasture access together with farm-level lameness prevalence, farm-level prevalence of hock lesions, herd size, parity, and farm-level milk fat appeared to be important covariates. The stratification of the analysis by study region allows for the extrapolation of the results to similar settings of dairy husbandry. The local, region-specific modelling of F. hepatica presence in this work contributes to the understanding of on-farm aspects of F. hepatica appearance. The applied technique represents a novel approach in this context to model epidemiological data on fasciolosis which allows for the identification of farms at risk and together with additional findings in regard to the epidemiology of fasciolosis, can facilitate risk assessment and deepen our understanding of on-farm drivers of the occurrence of F. hepatica

Non-linear change in body condition score over lifetime is associated with breed in dairy cows in Germany

Optimal body condition is crucial for the well-being and optimal productivity of dairy cows. However, body condition depends on numerous, often interacting factors, with complex relationships between them. Moreover, most of the studies describe the body condition in Holstein cattle, while condition of some breeds, e.g. Simmental (SIM) and Brown Swiss (BS) cattle, have not been intensively studied yet. Body condition score (BCS) proved to be one of the most effective measures for monitoring body condition in dairy cows. Alterations in BCS were previously mainly studied over a single lactation period, while changes over the lifetime were largely ignored. This study was designed to report BCS of German SIM and BS cows in the light of the broadly accepted BCS in German Holstein (GH) cows and to explore patterns of change in BCS over the productive lifetime of animals. BCS was modeled via linear mixed effects regression, over- and undercondition of animals were studied using mixed effects logistic regressions and condition of animals was explored with the multinomial log-linear model via neural networks. All models included an interaction between breed and age. We found BCS of SIM and BS to be higher than BCS of GH. Our results show that BCS of BS cows did not change over the lifetime. In contrast, the BCS of GH and SIM was found to have a non-linear (quadratic) shape, where BCS increased up to the years of highest productivity and then decreased in aging cows. Patterns of change between SIM and GH, however, differed. GH do not only reach their highest BCS earlier in life compared to SIM, but also start to lose their body condition earlier. Our dataset revealed that 23% of the animals scored were over- and 14% underconditioned. The proportion of cows that were overconditioned was high (>10% of cows) for every breed and every age, while severe underconditioning (>10% of cows) occurred only in middle aged and old GH. Moreover, we found that the probability of underconditioning of animals over lifetime increases, while the overconditioning decreases from the middle to older ages. Our findings highlight the importance of understanding the non-linear nature of BCS, and uncover the potential opportunity for improving the performance and welfare of dairy cows by adjusting their nutrition, not only during lactation, but also highly specific to breed and age

Identifying cow – level factors and farm characteristics associated with locomotion scores in dairy cows using cumulative link mixed models

Lameness is a tremendous problem in intensively managed dairy herds all over the world. It has been associated with considerable adverse effects on animal welfare and economic viability. The majority of studies have evaluated factors associated with gait disturbance by categorising cows into lame and non-lame. This procedure yet entails a loss of information and precision. In the present study, we extend the binomial response to five categories acknowledging the ordered categorical nature of locomotion assessments, which conserves a higher level of information. A cumulative link mixed modelling approach was used to identify factors associated with increasing locomotion scores. The analysis revealed that a low body condition, elevated somatic cell count, more severe hock lesions, increasing parity, absence of pasture access, and poor udder cleanliness were relevant variables associated with higher locomotion scores. Furthermore, distinct differences in the locomotion scores assigned were identified in regard to breed, observer, and season. Using locomotion scores rather than a dichotomised response variable uncovers more refined relationships between gait disturbances and associated factors. This will help to understand the intricate nature of gait disturbances in dairy cows more deeply

Associations of cow and farm characteristics with cow-level lameness using data from an extensive cross-sectional study across 3 structurally different dairy regions in Germany

The aim of the present study was to evaluate the associations between milk recording data, body condition score (BCS), housing factors, management factors, and lameness in freestall-housed dairy cows in 3 structurally different regions in Germany. These regions substantially vary regarding herd size, breeds, access to pasture, farm management (family run or company owned), and percentage of organic farms. The data used was collected in a large cross-sectional study from 2016 to 2019. A total of 58,144 cows from 651 farms in 3 regions of Germany (North, East, and South) was scored for locomotion and body condition. Additionally, data on milk yield, milk composition, breed, age, as well as information on housing and management were retrieved. One mixed-logistic regression model was fitted per region to evaluate the association of the data with the target variable “lame” and to allow for a comprehensive reflection across different kinds of farming types. In all regions, undercondition (BCS lower than recommended for the lactation stage; North: odds ratio [OR] 2.15, CI 1.96–2.34; East: OR 2.66, CI 2.45–2.88; South: OR 2.45, CI 2.01–2.98) and mid-lactation stage (102–204 d in milk; North: OR 1.15, CI 1.05–1.27; East: OR 1.24, CI 1.17–1.32; South: OR 1.38, CI 1.18–1.62) were associated with higher odds for lameness, whereas overcondition (BCS higher than recommended for the lactation stage; North: OR 0.51, CI 0.44–0.60; East: OR 0.51, CI 0.48–0.54; South: OR 0.65, CI 0.54–0.77) and parity of 1 or 2 was associated with lower odds (parity 1 = North: OR 0.32, CI 0.29–0.35; East: OR 0.19, CI 0.18–0.20; South: OR 0.28, CI 0.24–0.33; parity 2 = North: OR 0.51, CI 0.47–0.46; East: OR 0.41, CI 0.39–0.44; South: OR 0.49, CI 0.42–0.57), irrespective of the regional production characteristics. Low energy-corrected milk yield was associated with higher odds for lameness in South and North (North: OR 1.16, CI 1.05–1.27; South: OR 1.43, CI 1.22–1.69). Further factors such as pasture access for cows (North: OR 0.64, CI 0.50–0.82; and South: OR 0.65, CI 0.47–0.88), milk protein content (high milk protein content = North: OR 1.34, CI 1.18–1.52; East: OR 1.17, CI 1.08–1.28; low milk protein content = North: OR 0.79, CI 0.71–0.88; East: OR 0.84, CI 0.79–0.90), and breed (lower odds for “other” [other breeds than German Simmental and German Holstein] in East [OR 0.47, CI 0.42–0.53] and lower odds both for German Holstein and “other” in South [German Holstein: OR 0.62, CI 0.43–0.90; other: OR 0.46, CI 0.34 – 0.62]) were associated with lameness in 2 regions, respectively. The risk of ketosis (higher odds in North: OR 1.11, CI 1.01–1.22) and somatic cell count (higher odds in East: increased (>39.9 cells × 1,000/mL): OR 1.10; CI 1.03–1.17; high (>198.5 cells × 1,000/mL): OR 1.08; CI 1.01–1.06) altered the odds for lameness in 1 region, respectively. Cows from organic farms had lower odds for lameness in all 3 regions (North: OR 0.18, CI 0.11–0.32; East: OR 0.39, CI 0.28–0.56; South: OR 0.45, CI 0.29–0.68). As the dairy production systems differed substantially between the different regions, the results of this study can be viewed as representative for a wide variety of loose-housed dairy systems in Europe and North America. The consistent association between low BCS and lameness in all regions aligns with the previous literature. Our study also suggests that risk factors for lameness can differ between geographically regions, potentially due to differences in which dairy production system is predominantly used and that region-specific characteristics should be taken into account in comparable future projects

A machine learning approach using partitioning around medoids clustering and random forest classification to model groups of farms in regard to production parameters and bulk tank milk antibody status of two major internal parasites in dairy cows

Fasciola hepatica and Ostertagia ostertagi are internal parasites of cattle compromising physiology, productivity, and well-being. Parasites are complex in their effect on hosts, sometimes making it difficult to identify clear directions of associations between infection and production parameters. Therefore, unsupervised approaches not assuming a structure reduce the risk of introducing bias to the analysis. They may provide insights which cannot be obtained with conventional, supervised methodology. An unsupervised, exploratory cluster analysis approach using the k–mode algorithm and partitioning around medoids detected two distinct clusters in a cross-sectional data set of milk yield, milk fat content, milk protein content as well as F. hepatica or O. ostertagi bulk tank milk antibody status from 606 dairy farms in three structurally different dairying regions in Germany. Parasite–positive farms grouped together with their respective production parameters to form separate clusters. A random forests algorithm characterised clusters with regard to external variables. Across all study regions, co–infections with F. hepatica or O. ostertagi, respectively, farming type, and pasture access appeared to be the most important factors discriminating clusters (i.e. farms). Furthermore, farm level lameness prevalence, herd size, BCS, stage of lactation, and somatic cell count were relevant criteria distinguishing clusters. This study is among the first to apply a cluster analysis approach in this context and potentially the first to implement a k–medoids algorithm and partitioning around medoids in the veterinary field. The results demonstrated that biologically relevant patterns of parasite status and milk parameters exist between farms positive for F. hepatica or O. ostertagi, respectively, and negative farms. Moreover, the machine learning approach confirmed results of previous work and shed further light on the complex setting of associations a between parasitic diseases, milk yield and milk constituents, and management practices

Associations of production characteristics with the on-farm presence of Fasciola hepatica in dairy cows vary across production levels and indicate differences between breeds

Fasciola hepatica is one of the economically most important endoparasites in cattle production. The aim of the present work was to evaluate the relevance of production level on the associations of on-farm presence of F. hepatica with farm-level milk yield, milk fat, and milk protein in Holstein cows, a specialised dairy breed, and in Simmental cows, a dual purpose breed. Furthermore, we investigated whether differential associations were present depending on breed. Data from 560 dairy farms across Germany housing 93,672 cows were analysed. The presence of F. hepatica antibodies was determined via ELISA on bulk tank milk samples. Quantile regression was applied to model the median difference in milk yield, milk fat, and milk protein depending on the interaction of breed and fluke occurrence. Whereas a reduction in milk yield (-1,206 kg, p < 0.001), milk fat (-22.9 kg, p = 0.001), and milk protein (-41.6 kg, p <0.001) was evident on F. hepatica positive German Holstein farms, only milk fat (-33.8 kg, p = 0.01) and milk protein (-22.6 kg, p = 0.03) were affected on F. hepatica positive German Simmental farms. Subsequently, production traits were modelled within each of the two breeds for low, medium, and high producing farms in the presence of F. hepatica antibodies and of confounders. On Holstein farms, the presence of F. hepatica seropositivity was associated with lower production, while on German Simmental farms such an association was less evident. This work demonstrates that production level is relevant when assessing the associations between the exposure to F. hepatica with production characteristics. Moreover, both models indicate a breed dependence. This could point towards a differential F. hepatica resilience of specialised dairy breeds in comparison with dual purpose breeds