Herd-level animal management factors associated with the occurrence of bovine neonatal pancytopenia in calves in a multicountry 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

Validation of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from UK Biobank

BackgroundCurrently in the United Kingdom, cardiovascular disease (CVD) risk assessment is based on the QRISK3 score, in which 10% 10-year CVD risk indicates clinical intervention. However, this benchmark has limited efficacy in clinical practice and the need for a more simple, non-invasive risk stratification tool is necessary. Retinal photography is becoming increasingly acceptable as a non-invasive imaging tool for CVD. Previously, we developed a novel CVD risk stratification system based on retinal photographs predicting future CVD risk. This study aims to further validate our biomarker, Reti-CVD, (1) to detect risk group of ≥ 10% in 10-year CVD risk and (2) enhance risk assessment in individuals with QRISK3 of 7.5-10% (termed as borderline-QRISK3 group) using the UK Biobank.MethodsReti-CVD scores were calculated and stratified into three risk groups based on optimized cut-off values from the UK Biobank. We used Cox proportional-hazards models to evaluate the ability of Reti-CVD to predict CVD events in the general population. C-statistics was used to assess the prognostic value of adding Reti-CVD to QRISK3 in borderline-QRISK3 group and three vulnerable subgroups.ResultsAmong 48,260 participants with no history of CVD, 6.3% had CVD events during the 11-year follow-up. Reti-CVD was associated with an increased risk of CVD (adjusted hazard ratio [HR] 1.41; 95% confidence interval [CI], 1.30-1.52) with a 13.1% (95% CI, 11.7-14.6%) 10-year CVD risk in Reti-CVD-high-risk group. The 10-year CVD risk of the borderline-QRISK3 group was greater than 10% in Reti-CVD-high-risk group (11.5% in non-statin cohort [n = 45,473], 11.5% in stage 1 hypertension cohort [n = 11,966], and 14.2% in middle-aged cohort [n = 38,941]). C statistics increased by 0.014 (0.010-0.017) in non-statin cohort, 0.013 (0.007-0.019) in stage 1 hypertension cohort, and 0.023 (0.018-0.029) in middle-aged cohort for CVD event prediction after adding Reti-CVD to QRISK3.ConclusionsReti-CVD has the potential to identify individuals with ≥ 10% 10-year CVD risk who are likely to benefit from earlier preventative CVD interventions. For borderline-QRISK3 individuals with 10-year CVD risk between 7.5 and 10%, Reti-CVD could be used as a risk enhancer tool to help improve discernment accuracy, especially in adult groups that may be pre-disposed to CVD

Relative contributions of neighbourhood and animal movements to Coxiella burnetii infection in dairy cattle herds

Q fever in dairy cattle herds occurs mainly after inhalation of contaminated aerosols generated from excreta by shedder animals. Propagation of Coxiella burnetii, the cause of the disease between ruminant herds could result from transmission between neighbouring herds and/or the introduction of infected shedder animals in healthy herds. The objective of this study were (i) to describe the spatial distribution C. burnetii-infected dairy cattle herds in two different regions: the Finistère District in France (2,829 herds) and the island of Gotland in Sweden (119 herds) and (ii) to quantify and compare the relative contributions of C. burnetii transmission related to neighbourhood and to animal movements on the risk for a herd to be infected. An enzyme - linked immunosorbent assay was used for testing bulk tank milk in May 2012 and June 2011, respectively. Only one geographical cluster of positive herds was identified in north-western Finistère. Logistic regression was used to assess the association of risk for a herd to test positively with local cattle density (the total number of cattle located in a 5 km radius circle) and the in-degree (ID) parameter, a measure of the number of herds from which each herd had received animals directly within the last 2 years. The risk for a herd to test positively was higher for herds with a higher local cattle density [odds ratio (OR) = 2.3, 95% confidence interval (CI) = 1.6-3.2, for herds with a local density between 100 and 120 compared to herds with a local density 60]. The risk was also higher for herds with higher IDs (OR = 2.3, 95% CI = 1.6-3.2, for herds with ID 3 compared to herds that did not introduce animals). The proportion of cases attributable to infections in the neighbourhood in high-density areas was twice the proportion attributable to animal movements, suggesting that wind plays a main role in the transmission

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

A new measure for probability based assessment of risk of disease introduction in animal networks

International audienceIn the design of surveillance of contagious livestock diseases, there is often a desire to target high risk herds. This paper presents a new method to assess herd disease risk in contact networks. By this method a probability of disease ratio (PDR) is calculated. This measure is an improvement to current network measures as it takes direction, temporal order, movement size and probability of disease into account, and can be used for e.g. risk-based surveillance, in the classification of herds in control programmes or in risk factor studies. The usefulness of this method is explored by calculation of different versions of the PDR for Swedish cattle herds in simulated datasets, real animal movement data, and results from a survey of Q-fever in dairy herd

A new measure for probability based assessment of risk of disease introduction in animal networks

International audienceIn the design of surveillance of contagious livestock diseases, there is often a desire to target high risk herds. This paper presents a new method to assess herd disease risk in contact networks. By this method a probability of disease ratio (PDR) is calculated. This measure is an improvement to current network measures as it takes direction, temporal order, movement size and probability of disease into account, and can be used for e.g. risk-based surveillance, in the classification of herds in control programmes or in risk factor studies. The usefulness of this method is explored by calculation of different versions of the PDR for Swedish cattle herds in simulated datasets, real animal movement data, and results from a survey of Q-fever in dairy herd

A novel method to identify herds with an increased probability of disease introduction due to animal trade

International audienceIn the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herd's increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies

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