Bovine viral diarrhea virus (BVDV) is a common pathogen of cattle herds that causes economic losses due to reproductive disorders in breeding cattle and increased morbidity and mortality amongst infected calves. Our objective was to evaluate the impact of BVDV spread on the productivity of a beef cow-calf herd using a stochastic model in discrete time that accounted for (1) the difference in transmission rates when animals are housed indoors versus grazing on pasture, (2) the external risk of disease introductions through fenceline contact with neighboring herds and the purchase of infected cattle, and (3) the risk of individual pregnant cattle generating persistently infected (PI) calves based on their stage in gestation. The model predicted the highest losses from BVDV during the first 3 years after disease was introduced into a naive herd. During the endemic phase, the impact of BVDV on the yearly herd productivity was much lower due to herd immunity. However, cumulative losses over 10 years in an endemic situation greatly surpassed the losses that occurred during the acute phase. A sensitivity analysis of key model parameters revealed that herd size, the duration of breeding, grazing, and selling periods, renewal rate of breeding females, and the level of numerical productivity expected by the farmer had a significant influence on the predicted losses. This model provides a valuable framework for evaluating the impact of BVDV and the efficacy of different control strategies in beef cow-calf herds.
The importance of biosecurity as a strategy to prevent and control infectious diseases has increased substantially over the last few decades. Several studies have reported a low implementation level of biosecurity measures (BSM), particularly in cattle farms. In addition, a recent study demonstrated that cattle farmers are well aware of the recommended BSM and recognize them as more effective (in terms of time and costs) than treatment for disease. Therefore, other factors must be considered when it comes to understanding the decision‐making process followed by a farmer regarding the adoption of BSM. This study analysed the possible influence of five mental constructs described in the health belief model (HBM) on the adoption of BSM and assessed the possible association of these constructs with different demographic and socio‐psychological factors. Through an online survey, 988 questionnaires were completed by cattle farmers originating from Belgium, France, Germany, Spain and the Netherlands. The study revealed that the actual implementation of the BSM seems to be significantly influenced by the farmers’ perception of the measures’ benefits and the perception of health responsibility. Both constructs are influenced by the farmers’ personality in terms of risk aversion and biosecurity knowledge. It was also found that organic farmers had a significantly lower perception of the BSM benefits and of their responsibility towards animal, public and environmental health when compared with other types of farmer. Organic farmers in this study seemed less likely to implement biosecurity measures. To increase the adoption of BSM by cattle farmers, it is therefore important to emphasise the actual evidence‐based benefits of the measures and to investigate further how to strengthen cattle farmers’ sense of responsibility towards animal, public and environmental health.
Atomic hydrogen is commonly used to clean GaAs surfaces. The goals of this work are to optimize the cleaning process and to control surface reactions in order to avoid decomposition of GaAs. Chemically polished GaAs (001) surfaces have been cleaned by thermally generated atomic hydrogen and analyzed by surface sensitive techniques. We propose an optimal process involving two exposures. The first one at room temperature etches As oxides. The second one at 300 °C completes the reduction of Ga oxides. We demonstrate that the variations of the ionization energy, work function, and Fermi level are very sensitive to the completion of the cleaning reaction. These parameters can be used to monitor surface reactions on-line in order to avoid excessive desorption of As and GaAs decomposition.
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