Use of Predicted Behavior from Accelerometer Data Combined with GPS Data to Explore the Relationship between Dairy Cow Behavior and Pasture Characteristics.

Our aim in this study was to investigate whether the behaviors of dairy cows on pasture, predicted with accelerometer data and combined with GPS data, can be used to better understand the relationship between behaviors and pasture characteristics. During spring 2018, 26 Holstein cows were equipped with a 3D-accelerometer and a GPS sensor fixed on a neck-collar for five days. The cows grazed alternatively in permanent and in temporary grasslands. The structural elements, soil moisture, slope and botanical characteristics were identified. Behaviors were predicted every 10 s from the accelerometer data and combined with the GPS data. The time-budgets expressed in each characterized zone of 8 m × 8 m were calculated. The relation between the time-budgets and pasture characteristics was explored with a linear mixed model. In the permanent grassland, dairy cows spent more time under a tree to ruminate (p < 0.001) and to rest (p < 0.001) and more time to graze in areas with Holcus lanatus (p < 0.001). In the temporary grassland, behavior was influenced by the external environment (presence of other animals on the farm; p < 0.05). Thus, this methodology seems relevant to better understand the relationship between the behaviors of dairy cows and grazing conditions to develop precision grazing.

Quantification of the increase in the frequency of early calving associated with late exposure to bluetongue virus serotype 8 in dairy cows: implications for syndromic surveillance.

A recent study evaluating whether reproductive data could be used for syndromic surveillance found an increased frequency of early calving (calving occurring a few days earlier than expected) in areas exposed to the Bluetongue virus serotype 8 (BTV-8) in northern Europe. A high proportion of herds infected during the 2006-2009 European outbreak were not reported through the surveillance system. The objectives of this study were (1) to quantify the increase in the frequency of early calving associated with the exposure to BTV-8 in late gestation and (2) to determine whether this association could be found in populations exposed to BTV-8 but without reported clinical signs. Increases in frequency of early calving were quantified for cows in herds located in the 2007 outbreak area in France, reported or not as cases. Increases were detected for cows in both categories of herds with a larger effect in herds reported after clinical signs. Moreover, the largest effect was found for exposures occurring during the latest stage of pregnancy, suggesting that BTV infection could trigger calving in cows in late gestation, a few days earlier than expected. This is the first study quantifying the association between a viral infection and a shortened pregnancy length (still within a normal range). The high magnitude of the increase in frequency of early calving, their occurrence in herds from infected areas but not reported, and the short time interval between exposure and the occurrence of the event confirm the interest of using early calving as an indicator for syndromic surveillance.

Can routinely recorded reproductive events be used as indicators of disease emergence in dairy cattle? An evaluation of 5 indicators during the emergence of bluetongue virus in France in 2007 and 2008.

In response to increasing risks of emerging infectious diseases, syndromic surveillance can be a suitable approach to detect outbreaks of such diseases across a large territory in an early phase. To implement a syndromic surveillance system, the primary challenge is to find appropriate health-related data. The objective of this study was to evaluate whether routinely collected dates of reproductive events in dairy cattle could be used to build indicators of health anomalies for syndromic surveillance. The evaluation was performed on data collected in France between 2003 and 2009. First, a set of 5 indicators was proposed to assess several types of reproductive disorders. For each indicator, the demographic coverage over the total number of cattle at risk was analyzed in time and space. Second, the ability to detect an emerging disease in an early phase was retrospectively evaluated during epidemics of bluetongue serotypes 1 and 8 (BTV-1, BTV-8) in France in 2007 and 2008. Reproductive indicators were analyzed weekly during these epidemics for each indicator in each infected French district (16 in 2007 and 50 in 2008 out of 94 districts). The indicators were able to detect the BTV epidemics despite their low demographic coverage on a weekly basis relatively to total number of cattle (median=1.21%; range=0-11.7%). Four indicators related to abortions, late embryonic death, and short gestations were abnormally elevated during both BTV epidemics. Median times to abnormal elevations in these indicators were 20 to 71 d after the first notification of clinical signs of BTV by veterinarians. These results demonstrate that reproduction data can be used as indicators of disease emergences, whereas in the specific case of these BTV epidemics, detection via these indicators was later than clinical detection by veterinarians. The emergence of bluetongue in 2007 in France was associated with gestations that were a few days shorter than expected. A short gestation indicator underwent high elevations relative to prior random fluctuations and was the earliest (out of the 4 indicators) to show abnormal elevations, making it possible to detect this emergence.

Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection.

A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a 'guide towards substantiating freedom from infection' that describes both all assumptions-limitations and available methods that can be applied in different settings.

Assessing the reliability of innovative criteria to certify that cattle are non-Persistently Infected (non-PI) with the Bovine Viral Diarrhoea Virus (BVDV).

Persistently Infected (PI) animals play a central role in the transmission of BVDV infection between cattle herds. Thus, promoting the certification of non-PI animals is a relevant approach for improving control, as it contributes to securing the trade. The objectives of this study were: i) to assess the reliability of diverse certification criteria, and ii) to identify risk factors for erroneous certification. To do so, the proportion of animals wrongly certified as non-PI on the basis of tests performed after the certification date, was calculated for each criterion. The data used were collected in herds located in Brittany, involved in either a clearance process for those that were infected, or in a surveillance process for herds that were BVDV-free. A total of 23 criteria were defined by combining the technical characteristics of the tests (individual vs. pool; single vs. repeated; direct vs. indirect tests), and some pathogenic characteristics of BVDV infection. Overall, the rates of wrongly-certified animals were low (mean: 1.3 10-4). Direct and indirect criteria had equivalent performances. Heifers from birth, and even foetuses in the last third of gestation, are certified, provided that the herd to which they belong has been free of BVDV for more than 2.5 years. The risk for wrong certification increased in the case of PIs present in the herd or its surroundings. The simplicity of the output-based approach described here, and the excellent performance of indirect criteria relying on serological monitoring of BTM, make it particularly interesting, as its use could facilitate trade between countries.

Development of a syndromic surveillance system for Irish dairy cattle using milk recording data.

In the last decade and a half, emerging vector-borne diseases have become a substantial threat to cattle across Europe. To mitigate the impact of the emergence of new diseases, outbreaks must be detected early. However, the clinical signs associated with many diseases may be nonspecific. Furthermore, there is often a delay in the development of new diagnostic tests for novel pathogens which limits the ability to detect emerging disease in the initial stages. Syndromic Surveillance has been proposed as an additional surveillance method that could augment traditional methods by detecting aberrations in non-specific disease indicators. The aim of this study was to develop a syndromic surveillance system for Irish dairy herds based on routinely collected milk recording and meteorological data. We sought to determine whether the system would have detected the 2012 Schmallenberg virus (SBV) incursion into Ireland earlier than conventional surveillance methods. Using 7,743,138 milk recordings from 730,724 cows in 7037 herds between 2007 and 2012, linear mixed-effects models were developed to predict milk yield and alarms generated with temporally clustered deviations from predicted values. Additionally, hotspot spatial analyses were conducted at corresponding time points. Using a range of thresholds, our model generated alarms throughout September 2012, between 4 and 6 weeks prior to the first laboratory confirmation of SBV in Ireland. This system for monitoring milk yield represents both a potentially useful tool for early detection of disease, and a valuable foundation for developing similar tools using other metrics.

Meteorological and climatic variables predict the phenology of Ixodes ricinus nymph activity in France, accounting for habitat heterogeneity.

Ixodes ricinus ticks (Acari: Ixodidae) are the most important vector for Lyme borreliosis in Europe. As climate change might affect their distributions and activities, this study aimed to determine the effects of environmental factors, i.e., meteorological, bioclimatic, and habitat characteristics on host-seeking (questing) activity of I. ricinus nymphs, an important stage in disease transmissions, across diverse climatic types in France over 8 years. Questing activity was observed using a repeated removal sampling with a cloth-dragging technique in 11 sampling sites from 7 tick observatories from 2014 to 2021 at approximately 1-month intervals, involving 631 sampling campaigns. Three phenological patterns were observed, potentially following a climatic gradient. The mixed-effects negative binomial regression revealed that observed nymph counts were driven by different interval-average meteorological variables, including 1-month moving average temperature, previous 3-to-6-month moving average temperature, and 6-month moving average minimum relative humidity. The interaction effects indicated that the phenology in colder climates peaked differently from that of warmer climates. Also, land cover characteristics that support the highest baseline abundance were moderate forest fragmentation with transition borders with agricultural areas. Finally, our model could potentially be used to predict seasonal human-tick exposure risks in France that could contribute to mitigating Lyme borreliosis risk.

Corrigendum: Overview of Cattle Diseases Listed Under Category C, D or E in the Animal Health Law for Which Control Programmes Are in Place Within Europe.

[This corrects the article DOI: 10.3389/fvets.2021.688078.].

Key Learnings During the Development of a Generic Data Collection Tool to Support Assessment of Freedom of Infection in Cattle Herds.

Various European Member States have implemented control or eradication programmes for endemic infectious diseases in cattle. The design of these programmes varies between countries and therefore comparison of the outputs of different control programmes is complex. Although output-based methods to estimate the confidence of freedom resulting from these programmes are under development, as yet there is no practical modeling framework applicable to a variety of infectious diseases. Therefore, a data collection tool was developed to evaluate data availability and quality and to collect actual input data required for such a modeling framework. The aim of the current paper is to present the key learnings from the process of the development of this data collection tool. The data collection tool was developed by experts from two international projects: STOC free (Surveillance Tool for Outcome-based Comparison of FREEdom from infection, www.stocfree.eu) and SOUND control (Standardizing OUtput-based surveillance to control Non-regulated Diseases of cattle in the EU, www.sound-control.eu). Initially a data collection tool was developed for assessment of freedom of bovine viral diarrhea virus in six Western European countries. This tool was then further generalized to enable inclusion of data for other cattle diseases i.e., infectious bovine rhinotracheitis and Johne's disease. Subsequently, the tool was pilot-tested by a Western and Eastern European country, discussed with animal health experts from 32 different European countries and further developed for use throughout Europe. The developed online data collection tool includes a wide range of variables that could reasonably influence confidence of freedom, including those relating to cattle demographics, risk factors for introduction and characteristics of disease control programmes. Our results highlight the fact that data requirements for different cattle diseases can be generalized and easily included in a data collection tool. However, there are large differences in data availability and comparability across European countries, presenting challenges to the development of a standardized data collection tool and modeling framework. These key learnings are important for development of any generic data collection tool for animal disease control purposes. Further, the results can facilitate development of output-based modeling frameworks that aim to calculate confidence of freedom from disease.

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection.

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in <25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good", but risk factors and JD data were mostly evaluated as "fair." Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards.

Overview of Cattle Diseases Listed Under Category C, D or E in the Animal Health Law for Which Control Programmes Are in Place Within Europe.

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.

Standardizing output-based surveillance to control non-regulated cattle diseases: Aspiring for a single general regulatory framework in the European Union.

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.

Effects on milk quantity and composition associated with extruded linseed supplementation to dairy cow diets.

Enhanced milk composition can improve human health. The composition of milk determines its nutritional and market value. Therefore, in almost all pricing schemes the economic benefits obtained from raw milk sales are influenced by the milk yield and composition. The objective of this retrospective study was to quantify the average effects of supplementing extruded linseed, rich in α-linolenic acid, to dairy cows on milk yield and milk fat and protein content under field conditions. The study included test day records performed on cows from 1294 dairy herds during the period from 2008 to 2015 that were supplied at least 4 times with extruded linseed deliveries. Exposure statuses were defined according to the time sequence and the amount of extruded linseed distributed in the herd. The unexposed population was composed of cows being in a herd period when extruded linseed was not offered. In a linear dose-response relationship, every 100 g increase in exposure to EL was associated with an increased milk yield from 0.11 to 0.14 kg/day, decreased milk fat from 0.06 to 0.13 g/kg and decreased milk protein from 0 to 0.02 g/kg, according to the cow parity. This study provides information on the associations between estimated intakes of EL and milk production and composition using a large database obtained from commercial dairy herds.

STOC Free: An Innovative Framework to Compare Probability of Freedom From Infection in Heterogeneous Control Programmes.

The existence, stage of eradication and design of control programmes (CPs) for diseases that are not regulated by the EU differ between Member States. When freedom from infection is reached or being pursued, safe trade is essential to protect or reach that status. The aim of STOC free, a collaborative project between six countries, is to develop and validate a framework that enables a transparent and standardized comparison of confidence of freedom for CPs across herds, regions or countries. The framework consists of a model combined with a tool to facilitate the collection of the necessary parameters. All relevant actions taken in a CP are included in a Bayesian network model, which allows prior distributions for most parameters. In addition, frequency of occurrence and risk estimates for factors that influence either the probability of introduction or temporary misclassification leading to delayed detection of the infection are included in the model. Bovine viral diarrhea virus (BVDV) is used as an example disease. Many countries have CPs in place for BVDV and although elements of the CPs are similar, biosecurity measures and testing protocols, including types of tests and testing frequency, as well as target groups, differ widely. Although the initially developed framework is based on BVDV, the aim is to make it sufficiently generic to be adaptable to CPs for other diseases and possibly other species. Thus, STOC free will result in a single general framework, adaptable to multiple disease CPs, which aims to enhance the safety of trade.

Making Good Decisions on Dry Cow Management to Improve Udder Health - Synthesising Evidence in a Bayesian Framework.

The dry period is now recognised as a critical time for the control of clinical and sub-clinical mastitis in dairy cattle. Infections that occur, or that are not cured, during the dry period often result in clinical mastitis or raised somatic cell counts in early lactation. There is known to be large variability between herds in the patterns of dry period intramammary infections (IMI) and yet, until recently, there has been no information on farm determinants of the risk of IMI, other than in relation to dry cow treatments. In this paper we consider new research on cow characteristics, farm facilities and herd management strategies during the dry period in relation to clinical mastitis and raised somatic cell counts (SCC) in early lactation. We then describe, within a Bayesian framework, the concept of synthesising existing knowledge with new data to facilitate decision-making on dry cow management for individual farms.

Design and evaluation of multi-indicator profiles for targeted-selective treatment against gastrointestinal nematodes at housing in adult dairy cows.

Targeted-selective treatments against gastrointestinal nematode (GIN) in adult dairy cows require the identification of "cows to treat", i.e. cows whose milk production (MP) would increase after treatment. This study aimed at quantifying the ability of multi-indicator profiles to identify such cows. A randomized controlled clinical trial was conducted at housing in 25 French pasturing dairy herds. In each herd, treated cows received fenbendazole orally, control cows remained untreated. Daily MP was recorded and the MP variation between the pre- and post-visit periods was calculated (ΔMP) for each cow. ΔMP was modelled with control cows data (n=412) (piecewise linear mixed model). Estimated parameters were applied to treated cows data (n=414) to predict the expected ΔMP in treated cows if they had not been treated. Treated cows with an observed ΔMP (with treatment) higher than the expected ΔMP (without treatment) were labelled as "cows to treat". Herds where at least 50% of the young cows were "cows to treat" were qualified as "herds to target". To characterize such cows and herds, the available candidate indicators were (i) at the cow-level: parity, stage of lactation and production level, faecal egg count (FEC), serum pepsinogen level and anti-Ostertagia antibody level (expressed as ODR); (ii) at the herd-level: bulk tank milk (BTM) Ostertagia ODR, Time of Effective Contact (TEC, in months) with GIN infective larvae before the first calving, and percentage of positive FEC. These indicators were tested one-by-one or in combination to assess their ability to characterize "herds to target" and "cows to treat" (Chi-square tests). 115 out of 414 treated cows (27.8%) were considered as "cows to treat", and 9 out of 22 herds were qualified as "herds to target". The indicators retained to profile such cows and herds were the parity, the production level, the BTM Ostertagia ODR and the TEC. Multi-indicator profiles were much more specific than single indicator profiles, induced lower treatment rates, thereby minimizing the selection pressure on parasite populations. Particularly, to target a herd, the specificity was better with the profile "high BTM Ostertagia ODR and low-TEC" than with the BTM ODR value taken into account alone. The targeted-selective treatment of "young cows, belonging to herds with a high BTM ODR at housing and a low TEC" appeared as a pertinent solution, enabling a global approach for the control of GIN infection in which GIN control in heifers is connected to GIN control in adult cows.

Herd-level animal management factors associated with the occurrence of bovine neonatal pancytopenia in calves in a multi-country study.

Since 2007, mortality associated with a previously unreported haemorrhagic disease has been observed in young calves in several European countries. The syndrome, which has been named 'bovine neonatal pancytopenia' (BNP), is characterised by thrombocytopenia, leukocytopenia and a panmyelophthisis. A herd-level case-control study was conducted in four BNP affected countries (Belgium, France, Germany and the Netherlands) to identify herd management risk factors for BNP occurrence. Data were collected using structured face-to-face and telephone interviews of farm managers and their local veterinarians. In total, 363 case farms and 887 control farms were included in a matched multivariable conditional logistic regression analysis. Case-control status was strongly associated with the odds of herd level use of the vaccine PregSure® BVD (PregSure, Pfizer Animal Health) (matched adjusted odds ratio (OR) 107.2; 95% CI: 41.0-280.1). This was also the case for the practices of feeding calves colostrum from the calf's own dam (OR 2.0; 95% CI: 1.1-3.4) or feeding pooled colostrum (OR 4.1; 95% CI: 1.9-8.8). Given that the study had relatively high statistical power and represented a variety of cattle production and husbandry systems, it can be concluded with some confidence that no other herd level management factors are competent causes for a sufficient cause of BNP occurrence on herd level. It is suggested that genetic characteristics of the dams and BNP calves should be the focus of further investigations aimed at identifying the currently missing component causes that together with PregSure vaccination and colostrum feeding represent a sufficient cause for occurrence of BNP in calves.

Explaining variability in first grazing season heifer growth combining individually measured parasitological and clinical indicators with exposure to gastrointestinal nematode infection based on grazing management practice.

The objective of our study was to explain the variability of average daily weight gain (ADWG) due to gastrointestinal nematode (GIN) infection for 291 non treated first grazing season (FGS) heifers, from 12 independent groups in the western part of France, by combining parasitological and clinical indicators at individual level and grazing management indicators at group level. Parasitological indicators were faecal egg count (FEC), anti Ostertagia ostertagi antibody level (Ostertagia ODR), and pepsinogen level. Clinical indicators were diarrhea score (DISCO) and breech soiling score (BSS). At group level, grazing management practice (GMP), based on three variables (supplementation, month of turnout, grazing season duration), was clustered into three categories reflecting low, medium or high exposure (EXP) to GIN. Depending on the groups, turnout was from mid-March to early July and housing was from mid-October to late November, with a FGS duration ranging from 4 to 8.4 months. At turnout, the mean age of heifers was 8 months (range: 6-16 months) and they weighed between 175 and 268kg. In each GMP category, FEC significantly decreased between the mid-season and the housing, while Ostertagia ODR and pepsinogen level increased gradually throughout the grazing season. In contrast, clinical indicators did not show any seasonal variation. In a multivariate linear model, 22% of the ADWG variability was significantly explained by two individual indicators (Ostertagia ODR: 12.6%, DISCO: 4.8%) and by the group indicator (GMP category: 4.8%). ADWG losses due to GIN exposure (Ostertagia ODR) were estimated up to 39kg per heifer for the overall grazing season. For groups within the low EXP category the difference between animals with low (<697g/day) or high (>697g/day) ADWG was explained by the clinical indicator DISCO. In contrast, for groups within the medium and high EXP categories this difference was explained by a parasitological indicator (Ostertagia ODR). This study highlighted the value of combining both grazing management (group level) and parasitological (individual level) indicators to assess the impact of GIN on ADWG of FGS heifers. As a result, this combination might allow a better discrimination of animals or groups that may be in need of treatment in a targeting selective treatment approach.

Application of syndromic surveillance on routinely collected cattle reproduction and milk production data for the early detection of outbreaks of Bluetongue and Schmallenberg viruses.

This study aimed to evaluate the use of routinely collected reproductive and milk production data for the early detection of emerging vector-borne diseases in cattle in the Netherlands and the Flanders region of Belgium (i.e., the northern part of Belgium). Prospective space-time cluster analyses on residuals from a model on milk production were carried out to detect clusters of reduced milk yield. A CUSUM algorithm was used to detect temporal aberrations in model residuals of reproductive performance models on two indicators of gestation length. The Bluetongue serotype-8 (BTV-8) epidemics of 2006 and 2007 and the Schmallenberg virus (SBV) epidemic of 2011 were used as case studies to evaluate the sensitivity and timeliness of these methods. The methods investigated in this study did not result in a more timely detection of BTV-8 and SBV in the Netherlands and BTV-8 in Belgium given the surveillance systems in place when these viruses emerged. This could be due to (i) the large geographical units used in the analyses (country, region and province level), and (ii) the high level of sensitivity of the surveillance systems in place when these viruses emerged. Nevertheless, it might be worthwhile to use a syndromic surveillance system based on non-specific animal health data in real-time alongside regular surveillance, to increase the sense of urgency and to provide valuable quantitative information for decision makers in the initial phase of an emerging disease outbreak.

Evaluation of Two PCR Tests for Coxiella burnetii Detection in Dairy Cattle Farms Using Latent Class Analysis.

Different tests performed on bulk tank milk samples (BTM) are available to determine the C. burnetii status of herds. However, these tests, which are based on the detection of either antibodies directed against C. burnetii (ELISA) or bacterial DNA (PCR), have limitations. A currently disease-free herd infected in the past may continue to test positive with ELISA due to the persistence of antibodies in animals that were infected and that subsequently cleared the infection. Infectious herds can also be misclassified using PCR because of the absence of bacteria in the BTM when the test is performed. Recently, PCR has been used for bacterial DNA detection in the farm environment, which constitutes the main reservoir of C. burnetii. The objectives of this study were to assess and compare the sensitivities and specificities of one commonly used PCR test in BTM (PCR BTM) and of a PCR applied to environmental samples (PCR DUST) in dairy cattle farms. BTM and dust samples were collected (using environmental swabs) in 95 herds. The evaluation of the performance of the 2 tests was conducted using latent class models accounting for within herd disease dynamics. Parameter estimation was carried out using MCMC, within a Bayesian framework. Two types of priors were used for the specificity of PCR DUST. A model with a uniform prior on 0-1 fitted the data better than a model with a uniform prior on 0.95-1. With the best model PCR DUST had a lower sensitivity than PCR BTM (0.75 versus 0.83) and a specificity of 0.72. The moderately low value for the specificity of PCR DUST suggests that the presence of bacteria on farm is not always associated with persistent infections and shedding of bacteria in milk.