Comparison of the confidence in freedom from infection based on different control programmes between EU member states: STOC free

The STOC free project constructed a generic framework that allows a standardised and harmonised description of different control programmes (CP) for cattle diseases. The STOC free model can be used to determine the confidence of freedom from infection that has been achieved in disease CPs, in support of an ongoing assessment of progress towards output-based standards as outlined in the EU Animal Health Law. With this information, and as required, further CP actions can be taken to mitigate the risks of persistence and (re-)introduction on the probability of freedom from infection. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease because of the diversity in CPs in the six participating countries. A Bayesian hidden Markov model was considered the best modelling method. Detailed BVDVCP information was collected in the participating countries and the key aspects for inclusion in the STOCfree model were identified. A first version of STOC free model was developed and tested on simulated data. The risk factors for BVDV infection that needed to be included in the model were defined and default values for these risk factors were quantified. A data collection tool was finalised with which the data for the STOC free model was collected. Subsequently, the developed model was tested and validated using real BVDV CP data from partner countries. Based on the feedback, the model was finalised and the report and corresponding computer code were made publicly available. There were roughly three different BVDV situations that occurred in the partner countries: 1. Endemic situation with a CP operating at herd level, 2. Endemic situation with a CP operating at animal level and 3. BVD free situation. The STOC free model is able to include herd level data only and animal level data has to be aggregated to herd level before the model can be applied. The STOC free model is not applicable for a country that is completely BVDV free given that it needs some infections to estimate its parameters and converge. In the latter situation, a scenario tree model could be a better suited tool, and this was evaluated in the Swedish case study. Further work is needed for generalisation of the method to other diseases and expansion of the method to include socioeconomic aspects of CPs <br/

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

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

International audienceCountries 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 availabl

A living lab approach to understanding dairy farmers' needs of technologies and data to improve herd health: Focus groups from 6 European countries

For successful development and adoption of technology on dairy farms, farmers need to be included in the innovation process. However, the design of agricultural technologies usually takes a top-down approach with little involvement of end-users at the early stages. Living Labs offer a methodology that involve end-users throughout the development process and emphasize the importance of understanding users' needs. Currently, exploration of dairy farmers' needs of technologies has been limited to specific types of technology (e.g., smartphone apps) and adult cattle. The aim of this study was to use a Living Lab approach to identify dairy farmers' needs of data and technologies to improve herd health and inform innovation development. Eighteen focus groups were conducted with, in total, 80 dairy farmers from Belgium, Ireland, the Netherlands, Norway, Sweden, and the UK. Data were analyzed using Template Analysis and 6 themes were generated which represented the fundamental needs of autonomy, comfort, competence, community and relatedness, purpose, and security. Farmers favored technologies that provided them with convenience, facilitated their knowledge and understanding of problems on farm, and allowed them to be self-reliant. Issues with data sharing and accessibility, and usability of software were barriers to technology use. Furthermore, farmers were facing problems around recruitment and management of labor and needed ways to reduce stress. Controlling aspects of the barn environment, such as air quality, hygiene, and stocking density, was a particular concern in relation to youngstock management. In conclusion, the findings suggest that developers of farm technologies may want to include farmers in the design process to ensure a positive user experience and improve accessibility. The needs identified in this study can be used as a framework when designing farm technologies to strengthen need satisfaction and reduce any potential harm toward needs

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

Effectiveness of Passive and Active Surveillance for Early Detection of SARS-CoV-2 in Mink during the 2020 Outbreak in the Netherlands

Starting December 2019, a novel coronavirus (SARS-CoV-2) spread among humans across the world. From 2020 onward, farmed mink were found susceptible to the virus. In this paper, we describe the Dutch surveillance system and the added surveillance components for early detection of SARS-CoV-2 outbreaks and their results in Dutch mink farms. In the Netherlands, a surveillance system was in place in which mink farmers could submit carcasses for postmortem evaluation and could contact a telephone helpdesk for veterinary advise. Through this system, the first SARS-CoV-2 outbreak in two mink farms was detected in April 2020. Immediately, the Dutch Ministry of Agriculture commissioned a consortium of statutory and research institutes to intensify the surveillance system. The program consisted of both passive surveillance, i.e., mandatory notifications and active surveillance components, i.e., serological screenings and weekly risk-based sampling of dead mink for early detection of new SARS-CoV-2 infections. When one of the surveillance components indicated a suspicion of a possible SARS-CoV-2 infection, follow-up samplings were conducted and at confirmation, all mink were culled. During 2020, 67 out of 124 mink farms that were under surveillance became infected with SARS-CoV-2 (54%). Of these, 31 were detected based on clinical signs (passive surveillance of clinical signs) and 36 were detected through active surveillance. From the mink farms with a new SARS-CoV-2 outbreak that was detected through the surveillance, in 19% of the farms (n = 7), the mink never showed any clinical signs of SARS-CoV-2 and might have been missed by the passive notification system. This study underlines the added value of a surveillance system that can quickly be intensified. The subsequent combination of both passive and active surveillance has shown to be effective in the early detection of emerging pathogens, which is important to minimize the risk of zoonotic spill-over

Overview of cattle diseases listed under category C, D or E in the animal health law for wich control programmes are in place within Europe

13 páginas, 5 figuras, 3 tablas.The COST action “Standardising output-based surveillance to control non-regulated diseases of cattle in the European Union (SOUND control),” aims to harmonise the results of surveillance and control programmes (CPs) for non-EU regulated cattle diseases to facilitate safe trade and improve overall control of cattle infectious diseases. In this paper we aimed to provide an overview on the diversity of control for these diseases in Europe. A non-EU regulated cattle disease was defined as an infectious disease of cattle with no or limited control at EU level, which is not included in the European Union Animal health law Categories A or B under Commission Implementing Regulation (EU) 2020/2002. A CP was defined as surveillance and/or intervention strategies designed to lower the incidence, prevalence, mortality or prove freedom from a specific disease in a region or country. Passive surveillance, and active surveillance of breeding bulls under Council Directive 88/407/EEC were not considered as CPs. A questionnaire was designed to obtain country-specific information about CPs for each disease. Animal health experts from 33 European countries completed the questionnaire. Overall, there are 23 diseases for which a CP exists in one or more of the countries studied. The diseases for which CPs exist in the highest number of countries are enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis, bovine viral diarrhoea and anthrax (CPs reported by between 16 and 31 countries). Every participating country has on average, 6 CPs (min–max: 1–13) in place. Most programmes are implemented at a national level (86%) and are applied to both dairy and non-dairy cattle (75%). Approximately one-third of the CPs are voluntary, and the funding structure is divided between government and private resources. Countries that have eradicated diseases like enzootic bovine leukosis, bluetongue, infectious bovine rhinotracheitis and bovine viral diarrhoea have implemented CPs for other diseases to further improve the health status of cattle in their country. The control of non-EU regulated cattle diseases is very heterogenous in Europe. Therefore, the standardising of the outputs of these programmes to enable comparison represents a challenge.Peer reviewe

Cross-sectional study of the prevalence of and risk factors for hoof disorders in horses in The Netherlands

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