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.

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 maladies.

Como parte del proyecto europeo STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, herramienta de vigilancia para comparaciones por resultados respecto a la ausencia de infecciones, https://www.stocfree.eu), se confeccionó una herramienta de obtención de datos para facilitar la recogida normalizada de datos entrantes y se elaboró un modelo que posibilitara una comparación normalizada y armonizada de los resultados (datos salientes) de distintos programas de control de enfermedades bovinas. El modelo STOC free puede servir para calcular la probabilidad de ausencia de infección en los rebaños como parte de los programas de control y para determinar si estos programas se ajustan a las normas predefinidas de resultados de la Unión Europea. Como ejemplo de estudio para el proyecto se eligió el virus de la diarrea viral bovina (virus DVB) por la diversidad que presentaban los correspondientes programas de control de los seis países participantes. Empleando la herramienta de obtención de datos, se reunió información pormenorizada de los programas de control del virus DVB y los factores de riesgo. Para incluir los datos en el modelo STOC free, se cifraron unos aspectos clave y valores predeterminados Juzgando conveniente el empleo de un modelo oculto de Markov cuyos parámetros se estiman por inferencia bayesiana, se elaboró un modelo de esta índole aplicable a los programas de control del virus DVB. Para ensayar y validar el modelo se utilizaron datos reales de los programas de control del virus DVB de los países participantes, tras lo cual se hizo público el correspondiente código informático. El modelo STOC free trabaja con los datos por rebaño, aunque tras la agregación por rebaños pueden incluirse también datos por individuo. Para que este modelo sea aplicable a una enfermedad es preciso que esta sea endémica, pues el modelo requiere la presencia de cierto nivel de infección para calcular los parámetros y determinar convergencias. En aquellos países donde ya esté reconocida la ausencia de infección, sería más apropiado utilizar como herramienta un modelo de árbol de hipótesis. Los autores recomiendan ahondar en esta línea de trabajo para poder extender a otras enfermedades el uso del modelo STOC free.

Longevity and the association with cattle health in Dutch dairy farms.

Longevity of a herd is defined as the average age of all cattle over two years old at the moment of death (either natural, by euthanasia or by slaughter), and is increasing since 2018. The aim of this study was to evaluate the association between longevity and cattle health indicators in Dutch dairy herds. Anonymized census data were available for 16,200 Dutch dairy herds (∼98 % of the dairy herds) between 2016 and 2020. All herds were categorized into one of six longevity groups: herds with a high longevity (>seven years old), increasing longevity (mean increase of one year and two months between 2017 and 2020), median longevity (∼five years and eight months, without major fluctuations in longevity), decreasing longevity (mean decrease eight months), low longevity (

Output-based assessment of herd-level freedom from infection in endemic situations: Application of a Bayesian Hidden Markov model.

Countries have implemented control programmes (CPs) for cattle diseases such as bovine viral diarrhoea virus (BVDV) that are tailored to each country-specific situation. Practical methods are needed to assess the output of these CPs in terms of the confidence of freedom from infection that is achieved. As part of the STOC free project, a Bayesian Hidden Markov model was developed, called STOC free model, to estimate the probability of infection at herd-level. In the current study, the STOC free model was applied to BVDV field data in four study regions, from CPs based on ear notch samples. The aim of this study was to estimate the probability of herd-level freedom from BVDV in regions that are not (yet) free. We additionally evaluated the sensitivity of the parameter estimates and predicted probabilities of freedom to the prior distributions for the different model parameters. First, default priors were used in the model to enable comparison of model outputs between study regions. Thereafter, country-specific priors based on expert opinion or historical data were used in the model, to study the influence of the priors on the results and to obtain country-specific estimates. The STOC free model calculates a posterior value for the model parameters (e.g. herd-level test sensitivity and specificity, probability of introduction of infection) and a predicted probability of infection. The probability of freedom from infection was computed as one minus the probability of infection. For dairy herds that were considered free from infection within their own CP, the predicted probabilities of freedom were very high for all study regions ranging from 0.98 to 1.00, regardless of the use of default or country-specific priors. The priors did have more influence on two of the model parameters, herd-level sensitivity and the probability of remaining infected, due to the low prevalence and incidence of BVDV in the study regions. The advantage of STOC free model compared to scenario tree modelling, the reference method, is that actual data from the CP can be used and estimates are easily updated when new data becomes available.

Effect of selective dry cow treatment on udder health and antimicrobial usage on Dutch dairy farms.

Since 2013, selective dry cow treatment (SDCT) has been the standard approach in the Netherlands where farmers select cows for the use of antimicrobials at drying-off. Shortly after its introduction, antimicrobial usage decreased significantly, and no significant association was found between the level of SDCT and clinical mastitis (CM). Obviously, at that time long-term associations could not be evaluated. This study aimed to provide insight into the methods and level of implementation of SDCT on Dutch dairy farms with a conventional milking system (CMS) or an automatic milking system (AMS) in 2016 and 2017, several years after the implementation of SDCT. Udder health and antimicrobial use were also assessed. For this study, 262 farmers recorded dry cow treatments as well as all CM cases in the period from May 1, 2016, until April 30, 2017. Additionally, somatic cell count (SCC) data on cow and herd level, treatment data on herd level and questionnaire results on udder health management were collected. Data were analyzed using descriptive statistics with differences between milking systems being evaluated using nonparametric univariable statistics. In the study period, SDCT was applied on almost all (98.8%) of the participating dairy farms. The main reason for applying antimicrobials at drying-off was either the SCC history during the complete previous lactation or the SCC at the last milk recording before drying-off. The median percentage of cows treated with antimicrobials was 48.5%. The average incidence rate of CM was 27.3 cases per 100 cows per year. From all CM cases that were registered per herd, on average 32.8% were scored as mild, 42.2% as moderate, and 25.0% as severe CM. The mean bulk tank SCC of the herds was 168,989 cells/mL. A cow was considered to have subclinical mastitis (SCM) if individual SCC was ≥150,000 cells/mL for primiparous and ≥250,000 cells/mL for multiparous cows. Passing these threshold values after 2 earlier low SCC values was considered a new case of SCM. The mean incidence rate of SCM in these herds was 62.5 cases per 100 cows per year. Bulk tank SCC and the incidence rate of SCM on farms with a CMS were statistically lower than on farms with an AMS, whereas the incidence rate of CM did not significantly differ between both groups of farms. The AMS farms had more cows per herd treated with antimicrobials at drying-off and a larger proportion of severe CM cases than did CMS farms. It is unknown whether the differences are due to the milking system or to other differences between both types of farms. This study showed the level of adoption of SDCT, udder health, and antimicrobial usage parameters several years after the ban on the preventive use of antimicrobials in animal husbandry. It found that udder health parameters did not differ from those found in Dutch studies before and around the time of implementing SDCT, whereas SDCT was widely applied on Dutch dairy farms during the study period. Therefore, it was concluded that Dutch dairy farmers were able to handle the changed policy of antimicrobial use at drying-off while maintaining indicators of a good udder health.

Corrigendum: Control and Eradication Programs for Six Cattle Diseases in the Netherlands.

[This corrects the article DOI: 10.3389/fvets.2021.670419.].

Control and Eradication Programs for Six Cattle Diseases in the Netherlands.

Within the European Union, infectious cattle diseases are categorized in the Animal Health Law. No strict EU regulations exist for control, evidence of disease freedom, and surveillance of diseases listed other than categories A and B. Consequently, EU member states follow their own varying strategies for disease control. The aim of this study was to provide an overview of the control and eradication programs (CPs) for six cattle diseases in the Netherlands between 2009 and 2019 and to highlight characteristics specific to the Dutch situation. All of these diseases were listed as C,D or E in the New Animal Health Law. In the Netherlands, CPs are in place for six endemic cattle diseases: bovine viral diarrhea, infectious bovine rhinotracheitis, salmonellosis, paratuberculosis, leptospirosis, and neosporosis. These CPs have been tailored to the specific situation in the Netherlands: a country with a high cattle density, a high rate of animal movements, a strong dependence on export of dairy products, and a high-quality data-infrastructure. The latter specifically applies to the dairy sector, which is the leading cattle sector in the Netherlands. When a herd enters a CP, generally the within-herd prevalence of infection is estimated in an initial assessment. The outcome creates awareness of the infection status of a herd and also provides an indication of the costs and time to achieve the preferred herd status. Subsequently, the herd enrolls in the control phase of the CP to, if present, eliminate the infection from a herd and a surveillance phase to substantiate the free or low prevalence status over time. The high-quality data infrastructure that results in complete and centrally registered census data on cattle movements provides the opportunity to design CPs while minimizing administrative efforts for the farmer. In the CPs, mostly routinely collected samples are used for surveillance. Where possible, requests for proof of the herd status are sent automatically. Automated detection of risk factors for introduction of new animals originating from a herd without the preferred herd status i.e., free or unsuspected, is in place using centrally registered data. The presented overview may inspire countries that want to develop cost-effective CPs for endemic diseases that are not (yet) regulated at EU level.

The Northern Ireland Control Programmes for Infectious Cattle Diseases Not Regulated by the EU.

The disease control programmes for Bovine Viral Diarrhoea (BVD), Infectious Bovine Rhinotracheitis (IBR), Johne's Disease (JD), Leptospirosis and Neosporosis are described including the approved diagnostic tools, diagnostic quality systems, and the role of vaccination (where appropriate). This paper describes the control programmes within NI, the challenges relating them, as well as assessing their impact and effectiveness, taking into consideration the quality of data available and number of herds participating. With the NI agricultural industry experiencing increasing financial pressures and post Brexit changes, the necessity of working to maximise the performance of bovine disease control programmes at the individual farm level as well as at the regional level is increasingly important. The programmes described fall into two categories with two distinct aims. Two managed by Animal Health & Welfare NI (AHWNI), the BVD eradication and JD Dairy Control programmes seek to eradicate or control infection at the regional level. A further 5 programmes, covering BVD, JD, IBR, Leptospirosis and Neosporosis, are managed by the Agri-Food and Biosciences Institute (AFBI) and focus on facilitating eradication or control at the individual herd level. These latter programmes conform to the Cattle Health Certification Standards (UK) (CHeCS) which is a UK self-regulatory body set up to ensure consistency between different disease control schemes across herds. The largest of all the programmes described is the AHWNI BVD Eradication Programme which has led to significant reductions in infection incidence. Compliance with it has been high with more than 97% of all cattle alive at the end of 2020 having a BVD test status. The rolling annual incidence of BVD virus positive calves has fallen by 56% since the start of the compulsory programme in 2016. This decrease has occurred largely through industry initiatives to deal with BVD positives, including the voluntary culling of persistently infected (PI) animals by herd owners, a voluntary abattoir ban on the slaughter of BVD virus (BVDv) positive animals, and the inclusion of retention of a BVDv positive animal as a non-conformance in the industry-run Farm Quality Assurance Scheme.

Evaluation of the association between the introduction of data-driven tools to support calf rearing and reduced calf mortality in dairy herds in the Netherlands.

Between 2009 and 2017, calf mortality in the Dutch dairy sector showed a slight but steady increase. The Dutch dairy industry decided to act and supported the development of several data-driven tools that were implemented from 2018 on. The tools informed farmers about their calf mortality rates and stimulated them to improve. The Trend Analysis Surveillance Component of the Dutch cattle Health Surveillance System provided the possibility to evaluate the calf mortality in Dutch dairy herds before and after implementation of these tools. The aim of this study was to evaluate the association between calf mortality and i) all actions that were taken by the Dutch dairy industry to improve the quality of calf rearing and ii) other potential management or environmental factors associated with calf mortality in Dutch dairy herds. Census data from approximately 98 % of all Dutch dairy herds were available from July 2014 until June 2019. Four different calf mortality indicators were defined: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (ear-tagging till 14 d), preweaned calf mortality rate (15 d-55 d) and weaned calf mortality rate (56 d-1 yr.). All data were aggregated to herd and monthly level and were analysed using Population-Averaged Generalized Estimating Equations (PA GEE models) with a Poisson distribution and log link function. When the period before implementation of the tools (2016-2017) was compared to the period thereafter (2018-2019), all four calf mortality indicators decreased. The relative decrease varied from 3 % (postnatal calves) and 10 % (perinatal calves) up to 18 % and 30 % in preweaned and weaned calves, respectively. Registrations of veterinary treatments such as antimicrobial use, vaccinations (calf or cow) and antiparasitic treatments were associated with calf mortality. Additionally, herds with a higher level of metabolic problems in transition cows had a higher calf mortality and also extreme outside temperatures were associated with higher calf mortality. Given that the different tools were implemented nation-wide and a control group was lacking, we could not prove that implementing the different tools caused the reduction in calf mortality. We do however, believe that all the actions and communication towards improvement of calf rearing in dairy herds led to an increased awareness among farmers towards the importance of calf rearing management and therefore a reduction in calf mortality on national level.

Monitoring udder health on routinely collected census data: Evaluating the short- to mid-term consequences of implementing selective dry cow treatment.

In 2013, the preventive use of antimicrobials in Dutch livestock was prohibited, including a ban on the blanket application of antimicrobial dry cow treatment (BDCT). Since then, selective dry cow treatment (SDCT) has become the standard approach. In this study, we aimed to determine the effect of the ban on BDCT and the extent of the subsequent adoption of SDCT on antimicrobial usage (AMU) and udder health on Dutch dairy farms. In the Dutch cattle health surveillance system, AMU for dry cow treatment (AMUDCT), AMU for intramammary treatment at any point in time (AMUIMM), and udder health indicators are routinely and continuously monitored. This provided the opportunity to study associations among SDCT, udder health, and AMU on census data of approximately 17,000 dairy herds, with about 1.67 million cows in total (>2 yr old) at one moment in time in the period from 2013 until 2017. Six udder health parameters were evaluated using multivariable population-averaged generalized estimating equation models. The year in which the ban on BDCT was introduced (2013) was compared with the period thereafter (2014-2017). Additionally, AMUIMM and AMUDCT were included as independent variables to evaluate whether the extent to which SDCT was implemented on the herd level was associated with udder health. Demographic parameters were included as potential confounders. Since the ban on BDCT, overall declines of 63% in AMUDCT and 15% in AMUIMM were observed. The raw data show an improvement in 5 out of 6 evaluated udder health parameters between 2013 and 2017. Nevertheless, the multivariable model results showed that the period since the ban on BDCT was associated with a small but significant increase in the percentage of cows with high somatic cell count (HSCC) and new HSCC (+0.41% and +0.06%, respectively). Additionally, the probability of belonging to the group of herds with more than 25% of primiparous cows having HSCC during the start of lactation increased slightly, associated with the period after which BDCT was banned (odds ratio = 1.08). The probability of belonging to the group of herds with more than 25% cows having a persistent HSCC during the dry period was not affected and bulk milk somatic cell count showed a slight but significant reduction. The only udder health parameter that notably worsened during the study period was the probability of belonging to the group of herds with more than 25% of multiparous cows with a new HSCC after the dry period, during the start of lactation (odds ratio = 1.23). In herds where the farmer decided not to apply any dry cow therapy (≈20% of all herds), all udder health parameters were poorer compared with herds in which dry cow therapy was applied to some extent. The ban on BDCT and implementation of SDCT in the Netherlands was associated with a considerable reduction in AMU without a major impairment in udder health at the national level. Although negative effects of changed dry cow management were observed in some herds, we conclude that SDCT can be introduced without substantial negative effects on udder health.

Quantification of risk factors for bovine viral diarrhea virus in cattle herds: A systematic search and meta-analysis of observational studies.

Bovine viral diarrhea virus (BVDV) is endemic in many parts of the world, and multiple countries have implemented surveillance activities for disease control or eradication. In such control programs, the disease-free status can be compromised by factors that pose risks for introduction or persistence of the virus. The aim of the present study was to gain a comprehensive overview of possible risk factors for BVDV infection in cattle herds in Europe and to assess their importance. Papers that considered risk factors for BVDV infection in cattle were identified through a systematic search. Further selection of papers eligible for quantitative analysis was performed using a predefined checklist, including (1) appropriate region (i.e., studies performed in Europe), (2) representativeness of the study population, (3) quality of statistical analysis, and (4) availability of sufficient quantitative data. In total, 18 observational studies were selected. Data were analyzed by a random-effects meta-analysis to obtain pooled estimates of the odds of BVDV infection. Meta-analyses were performed on 6 risk factors: herd type, herd size, participation in shows or markets, introduction of cattle, grazing, and contact with other cattle herds on pasture. Significant higher odds were found for dairy herds (odds ratio, OR = 1.63, 95% confidence interval, CI: 1.06-2.50) compared with beef herds, for larger herds (OR = 1.04 for every 10 extra animals in the herd, 95% CI: 1.02-1.06), for herds that participate in shows or markets (OR = 1.45, 95% CI: 1.10-1.91), for herds that introduced cattle into the herd (OR = 1.41, 95% CI: 1.18-1.69), and for herds that share pasture or have direct contact with cattle of other herds at pasture (OR = 1.32, 95% CI: 1.07-1.63). These pooled values must be interpreted with care, as there was a high level of heterogeneity between studies. However, they do give an indication of the importance of the most frequently studied risk factors and can therefore assist in the development, evaluation, and optimization of BVDV control programs.

A description and qualitative comparison of the elements of heterogeneous bovine viral diarrhea control programs that influence confidence of freedom.

For endemic infections in cattle that are not regulated at the European Union level, such as bovine viral diarrhea virus (BVDV), European Member States have implemented control or eradication programs (CEP) tailored to their specific situations. Different methods are used to assign infection-free status in CEP; therefore, the confidence of freedom associated with the "free" status generated by different CEP are difficult to compare, creating problems for the safe trade of cattle between territories. Safe trade would be facilitated with an output-based framework that enables a transparent and standardized comparison of confidence of freedom for CEP across herds, regions, or countries. The current paper represents the first step toward development of such a framework by seeking to describe and qualitatively compare elements of CEP that contribute to confidence of freedom. For this work, BVDV was used as a case study. We qualitatively compared heterogeneous BVDV CEP in 6 European countries: Germany, France, Ireland, the Netherlands, Sweden, and Scotland. Information about BVDV CEP that were in place in 2017 and factors influencing the risk of introduction and transmission of BVDV (the context) were collected using an existing tool, with modifications to collect information about aspects of control and context. For the 6 participating countries, we ranked all individual elements of the CEP and their contexts that could influence the probability that cattle from a herd categorized as BVDV-free are truly free from infection. Many differences in the context and design of BVDV CEP were found. As examples, CEP were either mandatory or voluntary, resulting in variation in risks from neighboring herds, and risk factors such as cattle density and the number of imported cattle varied greatly between territories. Differences were also found in both testing protocols and definitions of freedom from disease. The observed heterogeneity in both the context and CEP design will create difficulties when comparing different CEP in terms of confidence of freedom from infection. These results highlight the need for a standardized practical methodology to objectively and quantitatively determine confidence of freedom resulting from different CEP around the world.

Quantifying calf mortality on dairy farms: Challenges and solutions.

In the Netherlands, the mortality rate of ear-tagged calves <1 yr is one of the indicators that is continuously monitored in census data and is defined as the number of deceased calves relative to the number of calf-days-at-risk. In 2017, yearly calf mortality rates were published in the lay press and resulted in discussions about the calculation of this parameter among stakeholders because the same parameter appeared to be calculated in many different ways by different organizations. These diverse definitions of calf mortality answered different aims such as early detection of deviations, monitoring trends, or providing insight into herd-specific results, but were difficult to understand by stakeholders. The aim of this study was to evaluate several definitions of calf mortality for scientific validity, usefulness for policymakers, and comprehensibility by farmers. Based on expert consultations, 10 definitions for calf mortality were evaluated that assessed different age categories, time periods, and denominators. Differences in definitions appeared to have a large effect on the magnitude of mortality. For example, with the original mortality parameter, the mortality rate was 16.5% per year. When the first year of life was subdivided into 3 age categories, the mortality rate was 3.3, 4.5, and 3.1% for postnatal calves (≤14 d), preweaned calves (15-55 d), and weaned calves (56 d-1 yr), respectively. Although it was logical that these mortality rates were lower than the original, the sum of the 3 separate mortality rates was also lower than the original mortality rate. The reason was that the number of calves present in a herd and the risk of mortality are not randomly distributed over a calf's first year of life and the conditional nature of mortality rates when calculated for different age categories. Ultimately, 4 parameters to monitor calf mortality in Dutch dairy herds were chosen based on scientific value, usefulness for monitoring of trends, and comprehensibility by farmers: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (≤14 d), preweaned calf mortality rate (15-55 d), and weaned calf mortality rate (56 d-1 yr). Slight differences in definitions of parameters can have a major effect on results, and many factors have to be taken into account when defining an important health indicator such as mortality. Our evaluation resulted in a more thorough understanding of the definitions of the selected parameters and agreement by the stakeholders to use these key indicators to monitor calf mortality.

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.

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.

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.

Veterinarians' attitudes toward antimicrobial use and selective dry cow treatment in the Netherlands.

In the Netherlands, regulations have been in place since 2008 to reduce the overall use of antimicrobials to mitigate antimicrobial resistance. As part of these regulations, a ban on the preventive use of antimicrobials, such as applying blanket dry cow treatment, was introduced and alternative measures such as selective dry cow treatment (SDCT) were implemented. Both farmers and veterinarians play an important role in implementing these measures and have a shared responsibility with respect to prudent antimicrobial use (AMU). The attitude of Dutch dairy veterinarians toward restricted AMU and toward SDCT is unknown, but a favorable attitude toward this approach seems crucial for successful implementation. In 2015, an online questionnaire was collected from 181 veterinarians that contained questions with regard to their attitude and behavior toward reduction of AMU and toward SDCT. Descriptive statistics were used to describe the data, and multivariable logistic regression models with a logit link function were applied to evaluate potential associations between veterinarians' attitudes toward AMU and SDCT and the rationale behind their mindset, based on positive and negative aspects of reduction in AMU. The veterinarians were divided into 3 groups based on their opinion on 4 statements with regard to AMU and SDCT: veterinarians with an unfavorable, a neutral, and a favorable attitude toward reduction of AMU and toward SDCT. For the multivariable logistic regression analysis, the first 2 groups were combined and compared with the veterinarians with a favorable attitude. The general attitude of Dutch dairy veterinarians toward reduction of AMU was positive, and most expressed the belief that they can still be a good veterinarian when they prescribe less antimicrobials. Veterinarians indicated they progressively promoted SDCT beginning in 2013. Most veterinarians see the advice they provide to farmers on SDCT as the best possible approach and are convinced that their farmers apply this SDCT approach. The results of the multivariable analyses showed that veterinarians with a favorable attitude mentioned positive aspects of SDCT, such as an increased consciousness of AMU among farmers, improving animal health, reducing antimicrobial resistance, and a chance to add value for the farmer, more often than other veterinarians. The latter group significantly more often indicated negative aspects of SDCT, such as a higher risk of sick cows and feeling pushed to follow the rules. In conclusion, the general attitude of Dutch dairy veterinarians toward reduction of AMU and SDCT was found to be positive. However, given the influence veterinarians potentially have on the attitude of farmers and the variability found in their attitude and behavior, veterinarians need specific attention if regional or national programs are organized trying to change behavior of farmers and encourage prudent AMU and SDCT.

Quantification of the probability of reintroduction of IBR in the Netherlands through cattle imports.

In the Netherlands, the feasibility of a national control program for infectious bovine rhinotracheitis (IBR) is discussed. The aim of this program would be to achieve freedom from BoHV1 circulation (the causal agent of IBR), in the Dutch cattle population. When IBR would be eradicated, maintaining the free status is essential and insight in the probability of introduction of IBR through cattle imports is crucial. Values for input parameters such as the number of imports per country of origin, herd level prevalence and probability that a random imported animal per age category was either acutely or latently infected with IBR were quantified. A stochastic simulation model was built to predict the basic risk and the efficacy of four risk mitigating scenarios were evaluated. These scenarios involved testing prior to import, import restrictions and vaccination. The model output predicted that IBR infected animals are imported regularly. In an IBR free situation, 571 (5th and 95th percentile: 431-781) cattle herds will be newly infected. Latent infections account for most newly infected herds (77%). When the virus in the imported latently infected animal does not reactivate, subsequent impact of such infections remains limited. The model predicted that most of the herds infected by introduction of acutely infected animals would be veal herds. The scenario in which imports were only allowed from status 9 or 10 countries combined with testing cattle that originated from status 9 countries was most effective in reduction of the import risk to 70 herds per year. The scenario in which vaccination of calves was combined with testing of older cattle was estimated to reduce the number of newly infected herds to 82 per year. The stakeholders classified the latter scenario as most realistic because this scenario was deemed both feasible and rather effective. This study did not evaluate the impact of introduction of IBR in the cattle population, which might differ depending on the type of infection (acute vs. latent) and the herd type in which the virus is introduced. Moreover, when making the final decision about the optimal intervention, the economic perspective should also be taken into account. This study predicted that introduction of IBR will remain a risk for the Dutch cattle population after virus circulation is eliminated from the Netherlands. The import risk is reduced most in scenarios in which testing and vaccination are combined.

A quantitative risk-analysis for introduction of Bovine Viral Diarrhoea Virus in the Netherlands through cattle imports.

Many countries have implemented control programmes aiming to eradicate Bovine Viral Diarrhoea Virus (BVDV). After obtaining the free status, a risk of re-introduction of the virus through import may remain. Therefore the risk of introduction of BVDV through cattle imports in the Netherlands was quantified and the effectiveness of subsequent intervention measures was assessed. Data, literature and expert opinion were used to estimate values for input parameters to feed a stochastic simulation model. The probability that BVDV was imported was differentiated into persistently infected (PI) cattle, trojan cows that transmitted the virus vertically resulting in a PI foetus (TR) and transient infected cattle (TI). The import risk was stratified to beef, dairy, small scale, suckler, trade, veal and young stock herds. The intervention scenarios that were evaluated consisted of virus testing, a combination of virus testing and antibody testing in pregnant cows, abolishment of imports from high risk countries (i.e. countries with a BVDV prevalence >15%) and a combination of import restrictions and testing prior to import. Each year, 334 (5th and 95th percentile: 65-902) Dutch cattle herds were estimated to be infected with BVDV through import. Veal herds account for most infections associated with import (87%), whereas in the other herd types, only 9 beef, 6 dairy, 2 small scale, 16 suckler, 10 trade and 2 young stock herds are infected through imports per year. Import of PI cattle is the most important risk for introduction in veal herds, while import of TR cows is the main source of BVDV introduction in dairy, small scale and suckler herds. With the intervention scenarios, the number of BVDV infected herds in the Netherlands could be reduced to 81 and 58 herds per year when respectively virus testing or a combination of virus and antibody testing was applied or to 108 herds when import from high risk countries was abolished. With the scenario in which both import from high risk countries was abolished combined with virus and antibody testing, the number of BVDV infected herds could be reduced to 17 herds per year. The risk assessment showed that BVDV is regularly imported in the Netherlands. The import risk can effectively be reduced by implementing diagnostic testing prior to import and only import cattle with a favourable result, eventually combined with certain trade restrictions.

Effectiveness and Cost Efficiency of Different Surveillance Components for Proving Freedom and Early Detection of Disease: Bluetongue Serotype 8 in Cattle as Case Study for Belgium, France and the Netherlands.

Quick detection and recovery of country's freedom status remain a constant challenge in animal health surveillance. The efficacy and cost efficiency of different surveillance components in proving the absence of infection or (early) detection of bluetongue serotype 8 in cattle populations within different countries (the Netherlands, France, Belgium) using surveillance data from years 2006 and 2007 were investigated using an adapted scenario tree model approach. First, surveillance components (sentinel, yearly cross-sectional and passive clinical reporting) within each country were evaluated in terms of efficacy for substantiating freedom of infection. Yearly cross-sectional survey and passive clinical reporting performed well within each country with sensitivity of detection values ranging around 0.99. The sentinel component had a sensitivity of detection around 0.7. Secondly, how effective the components were for (early) detection of bluetongue serotype 8 and whether syndromic surveillance on reproductive performance, milk production and mortality data available from the Netherlands and Belgium could be of added value were evaluated. Epidemic curves were used to estimate the timeliness of detection. Sensitivity analysis revealed that expected within-herd prevalence and number of herds processed were the most influential parameters for proving freedom and early detection. Looking at the assumed direct costs, although total costs were low for sentinel and passive clinical surveillance components, passive clinical surveillance together with syndromic surveillance (based on reproductive performance data) turned out most cost-efficient for the detection of bluetongue serotype 8. To conclude, for emerging or re-emerging vectorborne disease that behaves such as bluetongue serotype 8, it is recommended to use passive clinical and syndromic surveillance as early detection systems for maximum cost efficiency and sensitivity. Once an infection is detected and eradicated, cross-sectional screening for substantiating freedom of infection and sentinel for monitoring the disease evolution are recommended.

Prevalence and risk factors for extended-spectrum ß-lactamase or AmpC-producing Escherichia coli in organic dairy herds in the Netherlands.

Extended-spectrum ß-lactamase and AmpC-producing Escherichia coli (ESBL/AmpC) are an emerging problem and are hypothesized to be associated with antimicrobial use (AMU), and more specifically with the use of third- and fourth-generation cephalosporins. Whether ESBL/AmpC also occur in organic dairy herds, which have restricted AMU, is not known. Additionally, it is unknown whether, in addition to restricted AMU, other factors in organic herd management are associated with ESBL/AmpC herd status. The aim of this study was to estimate the prevalence of ESBL/AmpC in organic dairy herds in the Netherlands. Subsequently, the relationships between the ESBL/AmpC herd status and AMU and between ESBL/AmpC herd status and farmers' management were assessed in organic dairy herds. For this study, 90 randomly selected, officially registered organic dairy herds were included. The ESBL/AmpC herd status was determined based on the bacteriological culture result of a slurry sample. The sensitivity of testing slurry samples for ESBL/AmpC herd status is less than 100% for detecting herds with a low ESBL/AmpC prevalence. For that reason, herds that tested positive for ESBL/AmpC in slurry were defined as positive and herds with negative slurry samples were defined as unsuspected. A comprehensive questionnaire on management practices was conducted and records on specified antimicrobials that were provided to these herds by the veterinary service providers were obtained. From the data on antimicrobial supplies by the veterinarian, the animal daily defined dose of antimicrobials per farm per year (DDDAF) was calculated. Descriptive statistics were used to describe the relation between the ESBL/AmpC herd status and DDDAF. Multivariable logistic regression models were used to evaluate management factors associated with the ESBL/AmpC herd status. We found ESBL/AmpC in 12 of the 90 (13%; 95% confidence interval=7-22%) slurry samples from organic dairy herds. The median DDDAF in organic dairy herds was 0.5, which was not significantly different between ESBL/AmpC-positive and unsuspected dairy herds. No association could be found between the use of different types of antimicrobials, such as third- and fourth-generation cephalosporins, and ESBL/AmpC herd status. Factors that were associated with higher odds of being ESBL/AmpC-positive were pig farms located within a 2-km radius of the barn, applying parental treatment for clinical mastitis, and providing milk replacer to the female calves after colostrum intake. The prevalence of ESBL/AmpC in organic dairy herds appeared lower than the prevalence in previous studies conducted in conventional dairy herds. Apparently, ESBL/AmpC are also present in herds with low AMU; this indicates that other factors than AMU are also associated with ESBL/AmpC herd status.