Development of an objective and uniform scoring method to evaluate the quality of rearing in Dutch dairy herds.

Young stock rearing is an essential part of dairy management, and it is important that the quality of rearing can be monitored and altered if necessary. In this study, a young stock rearing quality system (KalfOK) was developed with the aim to provide an objective and standardized means to evaluate and monitor the quality of young stock rearing in Dutch dairy herds. In the project, 201 dairy farmers participated. Twelve key indicators were defined that were related to calving and successful rearing, antimicrobial use, and herd health. For each of the key indicators, the value was calculated per herd and quarter of the year between January 2014 and April 2017. Benchmark values were determined to compare herd-specific results and for selection of threshold values. Each of the key indicators was graded when the value scored above the threshold. Combining the grades resulted in the herd-specific KalfOK score, which could vary between 0 and 100. Subsequently, 100 of the participating dairy herds were visited and the quality of young stock rearing was scored by a trained veterinarian. Using principal component analysis, the results of the herd health checks were combined into a factor score that represented the observed quality of young stock rearing during the visit. The amount of variance in observed quality of rearing during the herd health check that was explained by the key indicators in KalfOK was evaluated. Additionally, the validity of KalfOK to distinguish herds with an excellent or insufficient quality of young stock rearing was assessed by comparing the top and bottom 10% herds in the herd health check with the proportion of herds with a KalfOK score above or below a prespecified cutoff value. The results of the linear regression model showed that the key indicators included in KalfOK accounted for 56% of the variation in the score of the herd visits by a veterinarian. The moving average of the annual KalfOK score, which was the sum of the grades of all key indicators, was 77 points (25th percentile = 71, 75th percentile = 85 points). The combination of the sensitivity (88%, 95% confidence interval = 47-100%) and specificity (67%, 95% confidence interval = 54-78%) of KalfOK to correctly classify herds with an excellent quality of young stock rearing was highest when a cutoff value of 80 points was applied. Detection of dairy herds with an insufficient quality of young stock rearing was best at a cutoff value of 70 points (sensitivity 86%, 95% confidence interval = 42-100%; specificity 77%, 95% confidence interval = 66-86%). The KalfOK score that was based on routinely collected herd data provided an indication of the quality of young stock rearing in individual Dutch dairy farms. The KalfOK score illustrates how such data can be transferred into herd-specific information in support of animal health and welfare. Given the increasing availability of automatically assembled data, the development of similar monitoring tools seems a feasible option to enhance herd-specific management.

Factors associated with high antimicrobial use in young calves on Dutch dairy farms: A case-control study.

Since 2012, the Dutch Veterinary Medicine Authority reports antimicrobial usage (AMU) in young calves (<56 d) on dairy farms on an annual basis. The AMU distribution in this age group is skewed, with a low AMU in young calves on the majority of dairy farms and a high AMU in a relatively small number of farms. This results in a notable difference between the mean and median AMU. To further reduce the mean AMU, the AMU on the high-AMU farms must be decreased. The objective of this study was to evaluate the association between both young stock management and an indication of the farmers' mindset and AMU in young calves on Dutch dairy farms with a high and low AMU in young calves. This knowledge may be helpful in decreasing AMU in young calves on high-AMU farms. We performed a case-control study in which 200 dairy farms (100 with high AMU and 100 with low AMU in young calves) participated. Case farms were defined as farms with an animal daily-defined dose at the farm level in young calves >28 in 2012 and 2013, based on the 90th percentile of the use of antimicrobials in young calves in 2012. Control farms had an animal daily-defined dose at the farm level in young calves of <0.5 in 2012 and 2013, which was determined to be low use. A questionnaire was conducted about general farm and young stock management, hygiene, housing, vaccination, and calf health. An indication of the farmers' mindset with regard to AMU and treatment of sick calves was determined by including statements (agree/disagree) in the questionnaire. In addition, routinely collected data on herd size, growth in herd size, replacement, and calf mortality were available for analysis. Dairy farmers that immediately started antimicrobial treatment in sick calves had higher odds of being in the high-AMU group than farmers who started treatment of sick calves with supportive nonantimicrobial therapy. Other variables associated with a high AMU in young calves included housing calves on partially slatted floors, a high prevalence of respiratory disease, an unfavorable Salmonella status, and not agreeing with the statement "Young stock need specific management." Both dairy farm management and opinions of dairy producers regarding AMU, indicative of mindset, are important when distinguishing farms with high and low AMU in young calves. Although the rationale behind mindset warrants more research, likely a change in both aspects seems to be required to reduce the AMU in young calves on dairy farms.

[Diarrhea and loss of production on Dutch dairy farms caused by the Schmallenberg virus]. / Diarree en productiedaling op Nederlandse melkveebedrijven door het Schmallenbergvirus.

At the end of August and the first two weeks of September 2011 dozens of veterinary practitioners reported to GD Veekijker (Animal Health Service) several dairy herds with cows with sudden decreased milk production, watery diarrhea and sometimes fever. In the beginning these reports came from the Eastern region of the Netherlands, after that also from the other three regions. The percentages of diseased herds per veterinary practice varied from a few till dozens per cent. Extensive bacteriological, virological and parasitological testing of the feces of sick cows did not reveal an infectious cause of the clinical problems. Recently, 50 stored blood samples of clinically diseased cattle were tested for the Schmallenbergvirus using a PCR, and 36% (18/50) tested positive. A large group of control cows (n=115) was also tested with the PCR and all cattle tested negative. Likely the Schmallenbergvirus was the primary cause of the clinical symptoms in the Dutch dairy herds. Further research will be done to confirm this.

Using routinely collected data to evaluate risk factors for mortality of veal calves.

From 2009 to 2012 a gradual increase in on-farm mortality of Dutch veal calves was observed. In 2012, the cattle industry decided that more information was needed on risk factors for mortality in both veal herds and herds of origin to enable implementation of risk mitigating measures. Routinely collected data were available from seven different data sources and contained information from 2.4 million white veal calves that were fattened in the period between 1 January 2011 and 30 June 2014. Survival analysis techniques (Kaplan-Meier), multilevel Poisson and multilevel Logistic regression models were applied to analyse the data. Two different models were assembled in which risk factors for veal calf mortality in respectively veal herds and herds of origin were identified. Univariable and multivariable regression techniques were used to detect risk factors significantly associated with mortality of veal calves during the fattening period. During the study period, the mean mortality was 4.9% per production cycle. The probability to die was highest during the first weeks after arrival in the veal herds and declined thereafter. Important risk factors included a veal herds with a higher use of antimicrobials, hair colour as proxy for breed, certain countries of origin, veal herd management with a limited amount of supplied feed and a not having an all-in / all-out system. A higher body weight at arrival in the veal herd was associated with lower mortality as well as veal calves that were fed an above median amount of milk, roughage and concentrates. From the calves that were fattened during the study period, observations of 1.1 million calves originated from the Netherlands and were available to study risk factors for veal calf mortality associated with the herd of origin. Important risk factors included purchase, herds with high mortality rates in the quarter in which the calf was born, fast growth in herd size, high cattle replacement rates and a higher antibiotic use in the quarter of birth. Calves that originated from herds that were certified BVD-free, Salmonella-unsuspected or Paratuberculosis-unsuspected, had a lower odds to die during the subsequent fattening period in a veal herd. Veal calf mortality was influenced by risk factors at the herd of origin as well as at veal herds. Adequate collaboration between the different industries is necessary to optimize veal calf management leading to a reduction in veal calf mortality during the fattening period.

Surveillance of cattle health in the Netherlands: Monitoring trends and developments using routinely collected cattle census data.

Since 2002, a national cattle health surveillance system (CHSS) is in place that consists of several surveillance components. The CHSS combines enhanced passive reporting, diagnostic and post-mortem examinations, random surveys for prevalence estimation of endemic diseases and quarterly data analysis. The aim of the data-analysis component, which is called the Trend Analysis Surveillance Component (TASC), is to monitor trends and developments in cattle health using routine census data. The challenges that were faced during the development of TASC and the merits of this surveillance component are discussed, which might be of help to those who want to develop a monitoring and surveillance system that includes data analysis. When TASC was developed, there were process-oriented challenges and analytical related issues that had to be solved. Process-oriented challenges involved data availability, confidentiality, quality, uniformity and economic value of the data. Analytical issues involved data validation, aggregation and modeling. Eventually, the results had to provide information on cattle health that was intuitive to the stakeholders and that could support decision making. Within TASC, both quarterly analysis on census data and, on demand, additional in-depth analysis are performed. The key monitoring indicators that are analyzed as part of TASC all relate to cattle health and involve parameters such as mortality, fertility, udder health and antimicrobial usage. Population-Averaged Generalized Estimating Equations, with the appropriate distribution (i.e. Gaussian, Poisson, Negative Binomial or Binomial) and link function (independent, log or logit), are used for analysis. Both trends in time and associations between cattle health indicators and potential confounders are monitored, discussed and reported to the stakeholders on a quarterly level. The flexibility of the in-depth analyses provides the possibility to conduct additional analyses when anomalies in trends of cattle health occur or when developments in the cattle industry need further investigation. In addition, part of the budget for the in-depth analysis can also be used to improve the models or add new data sources. The TASC provides insight in cattle health parameters, it visualizes trends in time, can be used to support or nuance signals that are detected in one of the other surveillance components and can provide warnings or initiate changes in policy when unfavorable trends occur.

A multidisciplinary approach to determine factors associated with calf rearing practices and calf mortality in dairy herds.

In the Netherlands, an increase in ear-tagged calf mortality (3 days to 1 year of age) in dairy farms was observed. The aim was to determine why calf mortality increased and how to reduce calf mortality in herds with structural high rates. A multi-disciplinary approach was chosen to study this phenomenon. First analysis of census data revealed that the majority of the calves died in the first month of life. In addition, a panel of 236 farmers indicated that the increase in calf mortality might be related to priority, time management and the mind-set of farmers. For that reason a questionnaire was carried out to detect risk factors for mortality among young calves (<1 month) in 100 dairy farms with increased calf mortality compared to 100 dairy farms with stable and below average calf mortality. The results showed that, besides management factors such as IBR and BVDV control, and purchase of cattle, also the answers to statements giving an indication on the farmers' mind-set, were associated with calf mortality. Therefore, a qualitative sociological study on the farmers' identity was conducted by performing in-depth interviews among 30 farmers with structurally high calf mortality rates. Afterwards, the results were communicated with a veterinary advisor who visited the farmers and gave tailored advice. Most of the interviewed farmers believed to have sufficient knowledge and skills regarding calf rearing. The farmers did not share their calf rearing problems with colleagues and advisors but they mentioned to be open to receive advice if not communicated in a reproaching or pedantic way. The sociologist distinguished three different phases of awareness concerning calf mortality among the farmers: (1) farmers who were only partly, or not at all, aware of high calf mortality; (2) farmers who felt powerless because of their inability to find a solution to their problems; and (3) farmers who knew they can be inaccurate when it comes to rearing calves, but were reluctant to change this. With the background information of the farmers' identity it was easier for the veterinary advisor to provide tailored advice resulting in a higher probability of following up. A first evaluation in which calf mortality rates in the six months after providing the advice were monitored, indicated that the advice resulted in reduced mortality. The combination of census data, epidemiological and qualitative sociological research revealed that advisors should be aware of the attitude and mind-set of the farmer and adapt their approach and advice accordingly.