Hair cortisol concentration in finishing pigs on commercial farms: variability between pigs, batches, and farms

Hair cortisol is a stress indicator and could be used to assess the pigs’ exposure to stressors in the weeks/months prior to non-invasive hair sampling. The main aim of this study was to describe the hair cortisol concentration (HCC) variability between individuals within a batch, between farms and between batches within a farm. The secondary aim was to determine how the number of sampled pigs influences the characterization of HCC within a batch. Twenty farrow-to-finish pig farms were recruited considering the diversity of their management practices and health status (data collected). Hair was sampled in two separate batches, 8 months apart. The necks of 24 finishing pigs were clipped per batch the week prior to slaughter. To describe the variability in HCC, an analysis of the variance model was run with three explanatory variables (batch, farm and their interaction). To identify farm clusters, a principal component analysis followed by a hierarchical clustering was carried out with four active variables (means and standard deviations of the two batches per farm) and 17 supplementary variables (management practices, herd health data). We determined how the number of sampled pigs influenced the characterization of HCC within a batch by selecting subsamples of the results. HCC ranged from 0.4 to 121.6 pg/mg, with a mean of 25.9 ± 16.2 pg/mg. The variability in HCC was mainly explained by differences between pigs (57%), then between farms (24%), between batches within the same farm (16%) and between batches (3%). Three clusters of farms were identified: low homogeneous concentrations (n = 3 farms), heterogeneous concentrations with either higher (n = 7) or lower (n = 10) HCC in batch 2 than in batch 1. The diversity of management practices and health statuses allowed to discuss hypotheses explaining the HCC variations observed. We highlighted the need to sample more than 24 pigs to characterize HCC in a pig batch. HCC differences between batches on six farms suggest sampling pigs in more than one batch to describe the HCC at the farm level. HCC variations described here confirm the need to study its links with exposure of pigs to stressors

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

AbstractIn 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

Factor modelling of multiple time series to detect temporal variations in common dynamics

International audienc

Méthodes statistiques en épidémiologie animale

International audienceThe main aim of veterinary epidemiology is to increase knowledge on both i) the dynamics and impact ofdiseases on animal production, health and welfare and on ii) the risk of animal-acquired (i.e. zoonoses) and food-bornediseases in humans. Because animals and animal products are the source of income for a large sector of society, theemphasis on economic aspects is much more important in veterinary epidemiology than in human epidemiology.Typical research questions deal with the identification of risk factors for a disease, the estimation of the impact of adisease on production, the evaluation of the efficacy of a treatment or the timely identification of disease occurrence. Forthese purposes, a wide range of statistical techniques are used and several types of data sources exist. One peculiarityin animal productions is the collection of large production related data such as daily milk productions, live weightsor reproduction data for example. These extremely large databases are both an asset and a challenge for statisticalmodelling. To illustrate the data sources and statistical methods used in veterinary epidemiology, we present part of thework conducted following the emergence of the bluetongue virus in cattle in 2006. First, we show how the impacts ofthe disease on milk production and reproduction were estimated. Then, in order to improve the timeliness of detectionof such emergences, the application of syndromic surveillance methods to the bluetongue emergence is presented.Finally, some knowledge gaps and directions for future work are presented.L’objectif principal de l’épidémiologie animale est de faire progresser les connaissances à la fois sur i) ladynamique et l’impact des maladies sur les productions, la santé et le bien-être des animaux ii) les risques pour lasanté humaine associés aux maladies animales transmissibles à l’homme (zoonoses) et aux toxi-infections alimentaires.Parce que les animaux et les produits animaux sont une source de revenus majeure pour une partie de la population, uneplace plus importante est accordée aux aspects économiques en épidémiologie animale qu’en épidémiologie humaine.Pour un trouble de santé, des questions de recherche classiques auront trait à l’identification de facteurs de risquede survenue du trouble, l’estimation de son impact sur la production, l’évaluation de l’efficacité d’un traitement ouencore la détection précoce de sa survenue. A ces fins, un large éventail de méthodes statistiques est utilisé et denombreuses sources de données existent. Une particularité des productions animales consiste en la collecte de grandsvolumes de données en lien avec la production tels que des productions laitières quotidiennes par vache, des poidsvifs ou des données de reproduction. Ces grands volumes de données disponibles représentent à la fois un avantageet une difficulté pour la modélisation statistique. Pour illustrer les sources de données et les méthodes utilisables enépidémiologie animale, nous présentons des travaux effectués suite à l’émergence de la fièvre catarrhale ovine en 2006.Dans un premier temps, nous montrons comment les impacts de la maladie sur la production laitière et la reproductionont été estimés. Puis, dans l’objectif d’améliorer la précocité de la détection de telles émergence, l’application desméthodes de surveillance syndromique est présentée. Enfin des besoins de connaissances et des perspectives pour defutures recherches sont présentés

Méthodes statistiques en épidémiologie animale

International audienceThe main aim of veterinary epidemiology is to increase knowledge on both i) the dynamics and impact of diseases on animal production, health and welfare and on ii) the risk of animal-acquired (i.e. zoonoses) and food-borne diseases in humans. Because animals and animal products are the source of income for a large sector of society, the emphasis on economic aspects is much more important in veterinary epidemiology than in human epidemiology.Typical research questions deal with the identification of risk factors for a disease, the estimation of the impact of a disease on production, the evaluation of the efficacy of a treatment or the timely identification of disease occurrence. For these purposes, a wide range of statistical techniques are used and several types of data sources exist. One peculiarity in animal productions is the collection of large production related data such as daily milk productions, live weights or reproduction data for example. These extremely large databases are both an asset and a challenge for statistical modelling. To illustrate the data sources and statistical methods used in veterinary epidemiology, we present part of the work conducted following the emergence of the bluetongue virus in cattle in 2006. First, we show how the impacts of the disease on milk production and reproduction were estimated. Then, in order to improve the timeliness of detection of such emergences, the application of syndromic surveillance methods to the bluetongue emergence is presented. Finally, some knowledge gaps and directions for future work are presented.L’objectif principal de l’épidémiologie animale est de faire progresser les connaissances à la fois sur i) la dynamique et l’impact des maladies sur les productions, la santé et le bien-être des animaux ii) les risques pour la santé humaine associés aux maladies animales transmissibles à l’homme (zoonoses) et aux toxi-infections alimentaires Parce que les animaux et les produits animaux sont une source de revenus majeure pour une partie de la population, une place plus importante est accordée aux aspects économiques en épidémiologie animale qu’en épidémiologie humaine. Pour un trouble de santé, des questions de recherche classiques auront trait à l’identification de facteurs de risque de survenue du trouble, l’estimation de son impact sur la production, l’évaluation de l’efficacité d’un traitement ou encore la détection précoce de sa survenue. A ces fins, un large éventail de méthodes statistiques est utilisé et de nombreuses sources de données existent. Une particularité des productions animales consiste en la collecte de grands volumes de données en lien avec la production tels que des productions laitières quotidiennes par vache, des poids vifs ou des données de reproduction. Ces grands volumes de données disponibles représentent à la fois un avantage et une difficulté pour la modélisation statistique. Pour illustrer les sources de données et les méthodes utilisables en épidémiologie animale, nous présentons des travaux effectués suite à l’émergence de la fièvre catarrhale ovine en 2006. Dans un premier temps, nous montrons comment les impacts de la maladie sur la production laitière et la reproduction ont été estimés. Puis, dans l’objectif d’améliorer la précocité de la détection de telles émergence, l’application des méthodes de surveillance syndromique est présentée. Enfin des besoins de connaissances et des perspectives pour de futures recherches sont présenté

Rearing system with nurse cows and risk factors for Cryptosporidium infection in Organic dairy calves

Rearing dairy calves with nurse cows has been increasingly adopted by French farmers especially in organic farming and is characterized by a fostering of two to four calves during the first month of life by an unmilked lactating cow. This type of rearing remains poorly documented regarding its impact on calf health, such as cryptosporidiosis. The objectives of our study were to describe practices related to rearing dairy calves with nurse cows and to evaluate the prevalence, intensity and risk factors for Cryptosporidium infection in calf neonates. Between January and September 2019, the rearing practices of calves were described in 20 organic French farms and faeces were sampled once from 611 animals aged between 5 and 21 days. Cryptosporidium oocyst shedding was identified by modified Ziehl-Neelsen technique and scored semi-quantitatively (score 0–4). The risk of excretion (score 0 versus 1–4) was analysed using multivariate logistic regression models.This cow-calf rearing system usually consisted of a first phase with the dam, followed by an optional phase of artificial milk feeding (calves being fed with whole milk of the farm) and a final phase of fostering by a nurse cow. Each nurse was suckled from one to five calves of close age with a fostering age of 8 days on average. The oocyst shedding prevalence was 40.2 % and similar to classically reared calves, but the intensity of shedding and the prevalence of diarrhoea appeared to be lower. The identified six risk factors for oocyst shedding were: born in the last two thirds of the birth order, born between January and July versus August and September, calf with its dam in the barn versus on pasture, having an artificial milk feeding phase versus being with the dam only, and contact between peer calves and notably the presence of an oocyst excretory calf fostered by the same nurse. These results emphasize the role of the environment for the direct and indirect contamination, particularly that related to the accumulation of oocysts from previous or peer calves facilitating the faecal-oral route of transmission. This highlights the crucial role of the premises used intensively during the winter and spring months with higher densities of calves in the barn compared to outdoor situations promoted by this rearing

Vermifugation des vaches laitières : impact sur la production et les paramètres d’objectivation du risque parasitaire

National audienceL'objectif de cette étude était d'évaluer, chez les vaches laitières adultes, l'évolution de la production laitière (PL) après traitement contre les strongles gastro-intestinaux (SGI) à la rentrée en stabulation, et d'en identifier les facteurs de variation, à l'échelle individuelle et à l'échelle troupeau. Un essai traitement (fenbendazole, Panacur10%) avec suivi de la PL journalière après traitement pendant 14 semaines a été mené à l'automne 2010 puis à l'automne 2011 dans 25 troupeaux bovins laitiers Prim'Holstein du Nord-Ouest de la France (541 vaches traitées, 547 vaches témoins). Le gain de PL moyen reste globalement modéré (maximum de +0,86 Kg/vache/jour en semaine 6 post-traitement, +0,28 Kg/vache/jour en moyenne sur 14 semaines de suivi). Les facteurs de variation les plus discriminants identifiés sont, à l'échelle troupeau, le temps de contact effectif des génisses avec les larves SGI (reflet de l'immunité des primipares) combiné au RDO anticorps anti-Ostertagia du lait de tank et le % de coproscopies positives dans le troupeau, et, à l'échelle individuelle, le RDO anticorps anti-Ostertagia sérique (les vaches à RDO faible répondant mieux au traitement). Ces résultats sont prometteurs pour établir une première clé d'intervention opérationnelle pour la mise en place de traitement sélectif contre les SGI chez les vaches adultes en troupeau laitier. L'analyse du temps de contact des génisses avec les SGI et donc indirectement l'analyse de la mise en place de l'immunité apparaît comme un socle de cette clé d'intervention

Dataset of hair cortisol concentration in 950 finishing pigs on 20 commercial farms

This dataset contains the hair cortisol concentrations of 950 finishing pigs. Pig hair was sampled as part of a study funded by the European project HealthyLivestock. Pigs were sampled in two separate batches on 20 farms (24 pigs/batch, two batches/farm. NB: 10 samples could not be analyzed at the laboratory). Farms were located in western France. A reference to the article relating to this dataset will be added when the article will be published. -The first sheet includes the 950 hair cortisol concentrations, distinguishing the batches and farms where pigs were sampled. -The second sheet includes the estimation of the average size of a pig batch on the 20 farms where hair was sampled + the estimation of the percentage of pigs sampled per batch

Evaluation of a continuous indicator for syndromic surveillance through simulation. application to vector borne disease emergence detection in cattle using milk yield.

Two vector borne diseases, caused by the Bluetongue and Schmallenberg viruses respectively, have emerged in the European ruminant populations since 2006. Several diseases are transmitted by the same vectors and could emerge in the future. Syndromic surveillance, which consists in the routine monitoring of indicators for the detection of adverse health events, may allow an early detection. Milk yield is routinely measured in a large proportion of dairy herds and could be incorporated as an indicator in a surveillance system. However, few studies have evaluated continuous indicators for syndromic surveillance. The aim of this study was to develop a framework for the quantification of both disease characteristics and model predictive abilities that are important for a continuous indicator to be sensitive, timely and specific for the detection of a vector-borne disease emergence. Emergences with a range of spread characteristics and effects on milk production were simulated. Milk yields collected monthly in 48 713 French dairy herds were used to simulate 576 disease emergence scenarios. First, the effect of disease characteristics on the sensitivity and timeliness of detection were assessed: Spatio-temporal clusters of low milk production were detected with a scan statistic using the difference between observed and simulated milk yields as input. In a second step, the system specificity was evaluated by running the scan statistic on the difference between observed and predicted milk yields, in the absence of simulated emergence. The timeliness of detection depended mostly on how easily the disease spread between and within herds. The time and location of the emergence or adding random noise to the simulated effects had a limited impact on the timeliness of detection. The main limitation of the system was the low specificity i.e. the high number of clusters detected from the difference between observed and predicted productions, in the absence of disease