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Whilst livestock management technologies may help to improve productivity, economic performance, and animal welfare on farms, there has been low uptake of technologies across farming systems and countries. This study aimed to understand dairy farmers' intention to use calf management technologies by combining partial least squares structural equation modelling (PLS-SEM) with qualitative comparative analysis (QCA). We evaluated the hypotheses that dairy farmers will intend to use calf technologies if they have sufficient competencies, sufficient materials, and positive meanings (e.g., attitudes or emotions) towards calf technologies, and they will not intend to use technologies if one of these elements is missing. An online survey was completed by 269 dairy farmers in Belgium, the Netherlands, Norway, and the UK. A PLS-SEM was developed, where the outcome was the number of calf management technologies that the respondent intended to use, and the latent constructs included meanings, materials, and competencies. QCA was then run separately for the datasets from each country. Intention to use technologies was the outcome, whereas positive meanings, sufficient materials, and sufficient competencies for technology use were conditions in the QCA. Evaluation of the PLS-SEM showed that reliability and validity of the latent constructs was appropriate for analysis. Assessment of the structural model indicated that having positive meanings regarding technologies significantly increased the number of calf technologies the farmer intended to use (β = 0.388, CI = 0.291 - 0.486). The QCA solutions show that the conditions for the intention to use, or not use, calf technologies differed between Belgium, the Netherlands, Norway, and the UK, but the presence (or absence) of positive meanings was consistently important. The solutions for Norway and Belgium aligned with our hypotheses, but the solutions for the Netherlands and UK did not. Some of the solutions exhibited features of causal complexity such as equifinality, conjunctural causation, and asymmetric causation, which would not be able to be easily identified using traditional regression analyses. This study highlights the causal complexity of technology use on farms as a social phenomenon. Furthermore, the study shows the usefulness of QCA for evaluating theoretical hypotheses regarding farmers' behaviour. We suggest that researchers could use this method to investigate other practices on farms that may have causal complexity., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Scenario tree modelling is a well-known method used to evaluate the confidence of freedom from infection or to assess the sensitivity of a surveillance system in detecting an infection at a certain design prevalence. It facilitates the use of data from various sources and the inclusion of risk factors into calculations, while still obtaining quantitative estimates of surveillance sensitivity and probability of freedom., Objectives: We conducted a scoping review to identify scenario tree models (STMs) applied to assess freedom from infection in veterinary medicine, characterize their use, parameterisation, reporting and potential limitations., Eligibility Criteria: We included published scientific articles and grey literature that were a) neither reviews nor expert opinions, b) aimed to assess freedom from infection, provided methods to assess it, or aimed to estimate the sensitivity of a surveillance program for early detection of an infection at a design prevalence, c) targeted infection in animals and d) used scenario tree modelling. The search covered documents published between January 2006 and August 2021., Design: Several search methods were used to retrieve scientific articles and grey literature relevant to the subject. The search strategy included searching in scientific databases and/or grey literature repositories, contacting experts across the world that previously worked with STMs and retrieving citations from relevant reviews., Results and Discussion: Four hundred twenty-four distinct documents were retrieved with our search string. After screening, data was extracted from 99 documents representing 67 projects. Forty different animal diseases were modelled with STMs, the most represented being infections with tuberculous Mycobacterium sp., Avian Influenza A virus and Brucella sp. STMs were mostly used for diseases of cattle, swine and wild mammals. Results showed that STMs were used in a large variety of studies, are very versatile and were used in disparate frameworks. However, we also found that studies are not reported in a standardized way and often lack important information. This makes results hard to interpret, compare and reproduce. Additionally, we identified common assumptions and misconceptions, the most important ones regarding sensitivity and specificity, which could have an impact on the results of the studies using STMs., Conclusion: We recommend the elaboration of internationally agreed guidelines about how to report results from STMs in a uniform manner. Such guidelines should include information on the study setting, procedures and analyses, but also on how the results could be interpreted concerning freedom from infection., Competing Interests: Declaration of Competing Interest None to declare. However, some of the authors and their respective teams have worked or still work with scenario tree models. The authors did not extract data from papers that they co-authored. The funder did not take part in the development or execution of the project., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Salmonella spp. infections in animals are a concern due to their zoonotic nature, welfare effects and economic impact on the livestock industry. To enable targeted surveillance, it is important to identify risk factors for the introduction of Salmonella spp. in a herd. Since 2009, Dutch dairy processors require herds delivering milk to their plants to participate in a Salmonella programme. In this programme, bulk milk is tested three times a year (i.e. test rounds) by ELISA on presence of antibodies against Salmonella spp. serogroups B and D. Based on these bulk milk results we identified newly infected herds, and aimed to identify associated risk factors. Effects of putative risk factors for becoming newly infected were studied using a multivariable population average logistic regression (PA-GEE) model with binomial distribution. Per test round in 2019-2021, 0.85-4.10 % of the Dutch dairy herds at risk became newly infected, with large regional differences. Several risk factors for becoming newly infected in the context of the low herd-level prevalence were identified. The most evident risk factors that were identified were having at least one infected or recently recovered dairy herd within 500 m (OR = 2.67), on-farm presence of pigs (OR = 1.63), introduction of more than 2 cattle from other herds in the previous 12 months (OR = 1.17), being in an area with a relative soil moisture of >0.54 % (OR = 1.31), being located in an area with a high water surface area (>2 %; OR = 1.14) and a larger herd size (OR = 1.65). These results indicate that, in addition to introduction of cattle, local transmission plays an important role in the between-herd transmission of Salmonella spp. Information on risk factors for becoming newly infected based on regularly collected data, can be used to improve surveillance and to implement targeted control measures against salmonellosis., Competing Interests: Declaration of Competing Interest None, (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

In September 2023, bluetongue virus serotype 3 (BTV-3) emerged in the Netherlands, infecting over five thousand livestock farms. In sheep, high morbidity and mortality rates were reported that were unlike previously described bluetongue outbreaks. This study aimed to quantify the impact of BTV-3 in the small ruminant population in the Netherlands in 2023. Sheep and goat movement census data and BTV-3 notification data were available from 2020 until the end of 2023. Data were aggregated to farm and week level and mortality indicators were calculated for lambs (<1 year) and adult animals (≥1 year). Population averaged GEE models with a Negative-binomial distribution and a log-link function correcting for repeated measures per farm in time were used to quantify the association between BTV-3 and mortality. In 2023, 2994 sheep farmers and 89 goat farmers notified clinical signs of BTV-3 to the NVWA. During this BTV-3 outbreak period, an additional 55,000 sheep died compared to the same period in 2020-2022. At flock level a high variety in mortality was observed, with a clear increase in mortality in both flocks that were not notified but that were located in infected areas and in flocks of which the farmer notified clinical signs. During the BTV-3 outbreak period, mortality in infected areas increased 4.2 (95 % CI: 4.0-4.3) times in sheep lambs (<1 year) and 4.6 (95 % CI: 4.4-4.8) times in sheep (≥1 year) compared to BTV-3 free areas. Flocks with a confirmed BTV-3 infection that were notified in September showed a 12.8 (95 % CI: 11.4-14.3) times higher mortality in lambs and a 15.1 (95 % CI: 13.7-16.6) times higher mortality in sheep compared to flocks in BTV-3 areas. In flocks of which the farmer notified clinical signs after September, mortality was 4.6 (95 % CI: 4.2-5.0) and 5.6 (95 % CI: 5.1-6.0) times higher in lambs and sheep compared BTV-3 areas respectively. In goats, around 4000 additional deaths were recorded during the BTV-3 outbreak period. In farms that were notified, mortality of goats (≥1 year) was 1.8 (95 % CI: 1.2-2.8) times higher compared to BTV-3 free areas. Since May 2024, multiple BTV-3 vaccines are available in the Netherlands. In June 2024, the first new infections of BTV-3 were confirmed in Dutch sheep flocks. Hopes are that with the possibility to vaccinate, the spread and impact of BTV-3 in the Netherlands will rapidly decline and that losses as observed in 2023 will no longer be seen., Competing Interests: Declaration of Competing Interest With this statement all authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

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 (

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., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Control programmes against non-regulated infectious diseases of farm animals are widely implemented. Different control programmes have different definitions of "freedom from infection" which can lead to difficulties when trading animals between countries. When a disease is still present, in order to identify herds that are safe to trade with, estimating herd-level probabilities of being infected when classified "free from infection" using field data is of major interest. Our objective was to evaluate the capacity of a Bayesian Hidden Markov Model, which computes a herd-level probability of being infected, to detect infected herds compared to using test results only. Herd-level risk factors, infection dynamics and associated test results were simulated in a population of herds, for a wide range of realistic infection contexts and test characteristics. The model was used to predict the infection status of each herd from longitudinal data: a simulated risk factor and a simulated test result. Two different indexes were used to categorize herds from the probability of being infected into a herd predicted status. The model predictive performances were evaluated using the simulated herd status as the gold standard. The model detected more infected herds than a single final test in 85 % of the scenarios which converged. The proportion of infected herds additionally detected by the model, compared to test results alone, varied depending on the context. It was higher in a context of a low herd test sensitivity. On average, around 20 %, for high test sensitivity scenarios, and 40 %, for low test sensitivity scenarios, of infected herds that were undetected by the test were accurately classified as infected by the model. Model convergence did not occur for 39 % of the scenarios, mainly in association with low herd test sensitivity. Detection of additional newly infected herds was always associated with an increased number of false positive herds (except for one scenario). The number of false positive herds was lower for scenarios with low herd test sensitivity and moderate to high incidence and prevalence. These results highlight the benefit of the model, in particular for control programmes with infection present at an endemic level in a population and reliance on test(s) of low sensitivity., (Copyright © 2022 Elsevier B.V. All rights reserved.)

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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Several European countries have implemented country specific programmes to control cattle diseases with little or no regulation in the European Union (EU). These control programmes vary between member states, impairing a confident comparison of freedom from disease when cattle originate from different countries. In order to facilitate safe trade, there is a need to support the development of transparent methods that enable comparison of outputs of surveillance, control or eradication programmes. The aim of the COST Action (CA 17110), Standardizing OUtput-based surveillance to control Non-regulated Diseases in the EU (SOUND control), is the development of a generic and joint understanding of the requirements and characteristics needed for a flexible output-based framework. This framework should be able to substantiate the confidence of disease freedom and cost-effectiveness of heterogeneous surveillance, control or eradication programmes for cattle diseases in the EU. This project supports other initiatives in the development of an output-based framework which will subsequently facilitate safe trade and support the improvement of disease control measures, which is of great importance as the cattle sector contributes to one third of the total gross production value of EU agriculture., (Copyright © 2020. Published by Elsevier B.V.)

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., (Copyright © 2018 Elsevier B.V. All rights reserved.)

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., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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., (Copyright © 2017. Published by Elsevier B.V.)

Information is scarce on the prevalence of hoof disorders in horses. In this study, we examined the prevalence of and risk factors for hoof disorders in a population of horses in The Netherlands. In a group of 942 randomly selected horses, hoof health was scored during regular foot trimming (one horse/farm). Hooves were assessed for the occurrence of one of 12 hoof disorders by a group of 21 certified farriers in two periods i.e. winter and summer of 2015. The mean age of the group of horses was 11.2±5.6years. They were mainly used for recreation (28.2%), dressage (26.8%), other disciplines (such as carriage driving and breeding) (18.7%), showjumping (17.6%) or combinations of these activities (8.6%). The horse farms studied were evenly distributed throughout the country. The horses were housed on different types of bedding, including straw (51.0%), shavings (17.5%), flax (16.1%) or other materials (11.0%), or were kept at pasture (4.4%). In 85% of the horses, at least one hoof disorder was observed during regular foot trimming. Most of the lesions were mild. The most frequently diagnosed hoof disorders were: thrush (T; 45.0%); superficial hoof wall cracks (SHWC; 30.4%); growth rings (GR; 26.3%); and sole bruises (SB; 24.7%). Less frequently observed hoof disorders included: perforating hoof wall cracks (PHWC; 16.4%); white line disease (WLD; 17.8%); and white line widening (WLW; 11.8%). Horizontal hoof cracks (5.2%), chronic laminitis (3.9%), quarter cracks (2.7%), keratoma (1.8%) and frog cancer (1.0%) were less frequently observed. Factors significantly associated with the occurrence of thrush comprised a wet stable floor (OR 1.6 and 2.9, for somewhat wet to wet respectively, compared to dry), the use of straw as bedding (OR=1.5, compared to flax), the housing strategy (e.g. permanent housing in contrast to permanent pasturing) (OR=1.7) and poor horn quality (OR=3.4). A higher prevalence of WLD was associated with less frequent hoof picking (OR=2.1 if performed weekly instead of daily), the use of flax bedding (OR=2.1, compared to straw) and poor horn quality (OR=8.1). A higher prevalence of SB was observed in horses used for multiple disciplines (OR=3.5, compared to dressage), with white-coloured hooves (OR=5.0, compared to black hooves), with longer intervals between trimming sessions (OR=4.8 in case of 8-10 weeks compared to weekly) and with poor horn quality (OR=5.4). A higher prevalence of WLW was observed in older horses (OR=15.5 for horses >19years, compared to <5years), in those with longer intervals between trimming sessions (OR=1.8 in case of 8-10 weeks compared to weekly), and in certain breeds (OR=3.2 for Friesian horses, 2.9 for Welsh ponies and 13.1 for Shetland ponies, all compared to Dutch Warmblood). In conclusion, although most of the hoof disorders identified were only in a mild stage, still an unexpectedly high prevalence of hoof disorders was observed during regular hoof trimming. Analysis of the data showed that some parameters, such as the use of flax bedding, may be protective for certain hoof disorders but a risk factor for others. This study provides useful guidelines for monitoring hoof health, reducing lameness and optimizing equine welfare., (Copyright © 2017 Elsevier B.V. All rights reserved.)

This study aimed at comparing the surveillance program of bovine herpesvirus type 1 (BHV1) as laid down by EU Decision 2004/558/EC and 2007/584/EC ('conventional design') with an alternative design. The alternative design was based on monthly bulk-milk testing, clinical surveillance and a risk-based component that involves testing of animals that are purchased from non-free cattle herds. Scenario-tree analyses were carried out to determine sensitivities of the surveillance system (and its components) and the monthly confidence of freedom on herd-level. Also, the expected costs per surveillance design and components thereof were calculated. Results showed that the conventional (EU) and alternative surveillance designs to obtain a BHV1-free status performed equally well in terms of sensitivity. However, total costs per cattle herd to obtain a free status were highest in the conventional design. In an endemic situation and with a within-herd design prevalence of 10%, the conventional design led to a varying probability of freedom ranging from 99.6% to 100% per month. With the alternative design, in this situation, a constant probability of freedom of >99.9% per month was found. In a disease-free situation, both designs performed equally well (probability of freedom >99.9% per month). The yearly costs per farm for monitoring the disease-free status decreased by approximately 25% in the alternative design. The alternative strategy based on monthly bulk-milk monitoring therefore was deemed most cost-effective. This study showed that the surveillance regime to attain and maintain a BHV1-free status as described by EU-legislation can be improved to reduce the monitoring costs without reduction of the system's sensitivity, given a within-herd design prevalence of 10%. The assessment of various surveillance designs could be highly useful to support decision-making towards a more risk-based approach of animal health surveillance., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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., (Copyright © 2016 Elsevier B.V. All rights reserved.)

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., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Schmallenberg virus (SBV), a novel orthobunyavirus that rapidly spread throughout north-western Europe in 2011, caused congenital malformations in lambs and goat kids (Van den Brom et al., 2012) and newborn calves (Hoffmann et al., 2012). The impact of the SBV epidemic seemed limited however, in terms of the number of affected herds with malformed offspring (European Food Safety Authority, 2012b). Nevertheless, little is known with regard to the overall within-herd impact of SBV infection. The objective of the current study was to quantify the impact of the 2011 SBV epidemic on the productivity of dairy cattle in the Netherlands and the district of Kleve, Germany. For the Netherlands, several multilevel multivariable statistical models were applied on eight productivity parameters regarding milk production, reproductive performance and mortality. All four fertility parameters analysed were slightly but significantly reduced between August 1st and November 1st 2011 compared to the reference period in 2009-2010. Between August 15th and September 19th 2011, the average loss in milk production per cow was -0.26kg (95% CI: -0.30; -0.22) per day in dairy herds, compared to the reference period (p<0.001). The total loss per cow in a subgroup of dairy herds that notified malformations in newborn calves during the mandatory notification period in the Netherlands was -0.43kg (95% CI: -0.59; -0.28) per day (p<0.001). For Germany, a study was carried out in the district of Kleve, situated in the state of North Rhine-Westphalia near the Dutch border. Data on milk yield, two fertility parameters and the number of rendered calves in this specific region were analysed. There was a small but significant increase in the number of secondary and third inseminations between August 1st and November 1st 2011, indicating reduced fertility. No significant change in calf mortality was observed in the assumed SBV period. Milk production at district level did not seem to be affected by SBV in August and September 2011. SBV had no or limited impact on mortality rates, which was as expected given the relatively mild expression of SBV in adult cows and the low incidence of notified malformations in newborn calves. Our results indicate that SBV had a limited impact on productivity of dairy cattle. However, the total economic impact of SBV on the ruminant industry not only consists of productivity caused losses; it is expected that international trade restrictions formed a larger part of the total economic impact., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Bluetongue virus serotype 8 (BTV-8) emerged in north-western Europe in 2006. In 2007, one of the affected countries (the Netherlands) implemented a sentinel network in dairy cattle. This data offered the opportunity to estimate transmission parameters. From our field data, the number of secondary infected cows that became infected by one infectious cow in a completely susceptible herd through the bites of infectious Culicoides i.e. the basic reproduction ratio (R(0)) was calculated. With that information, the R(0) of BTV-8 was estimated using an formulae of a general SIR model. In 2007, the BTV-8 epidemic started in the south and spread northwards in the following months. R(0) could be estimated for 197 herds in which transmission occurred. The median R(0) was 2.3 and the mean R(0) was 3.7 (5th percentile=1.8; 95th percentile=11.0). In the northern region where BTV-8 transmission occurred later in the season with less favorable conditions for transmission, R(0) remained significantly lower than in the south. Our model differed from earlier published more theoretical models on BTV-8 transmission because we estimated transmission from serological field data while other models used literature based assumptions for the majority of the parameters included in their models. Although there were many differences between our model and the previously developed more theoretical models, the results showed similar ranges of R(0) for BTV-8. The reasons for the similarity between the results may be that, although the part of the vector was not included with parameters in our model, the transmission based on serological field data in cows represented both BTV-8 transmission influenced by cows and by its vector, Culicoides. Furthermore, in the earlier models the assumptions made on the vector part, although derived from literature, probably gave a good representation of the true behavior of the Culicoides species that were associated with BTV-8 transmission in north-western Europe., (Copyright © 2012 Elsevier B.V. All rights reserved.)