Joining the dots - understanding the complex interplay between the values we place on wildlife, biodiversity conservation, human and animal health: A review.

The value of wildlife has long been ignored or under-rated. However, growing concerns about biodiversity loss and emerging diseases of wildlife origin have enhanced debates about the importance of wildlife. Wildlife-related diseases are viewed through these debates as a potential threat to wildlife conservation and domestic animal and human health. This article provides an overview of the values we place on wildlife (positive: socio-cultural, nutritional, economic, ecological; and negative: damages, health issues) and of the significance of diseases for biodiversity conservation. It shows that the values of wildlife, the emergence of wildlife diseases and biodiversity conservation are closely linked. The article also illustrates why investigations into wildlife diseases are now recognized as an integral part of global health issues. The modern One Health concept requires multi-disciplinary research groups including veterinarians, human physicians, ecologists and other scientists collaborating towards a common goal: prevention of disease emergence and preservation of ecosystems, both of which are essential to protect human life and well-being.

Evaluation of farm-level parameters derived from animal movements for use in risk-based surveillance programmes of cattle in Switzerland

BACKGROUND: This study focused on the descriptive analysis of cattle movements and farm-level parameters derived from cattle movements, which are considered to be generically suitable for risk-based surveillance systems in Switzerland for diseases where animal movements constitute an important risk pathway. METHODS: A framework was developed to select farms for surveillance based on a risk score summarizing 5 parameters. The proposed framework was validated using data from the bovine viral diarrhoea (BVD) surveillance programme in 2013. RESULTS: A cumulative score was calculated per farm, including the following parameters; the maximum monthly ingoing contact chain (in 2012), the average number of animals per incoming movement, use of mixed alpine pastures and the number of weeks in 2012 a farm had movements registered. The final score for the farm depended on the distribution of the parameters. Different cut offs; 50, 90, 95 and 99%, were explored. The final scores ranged between 0 and 5. Validation of the scores against results from the BVD surveillance programme 2013 gave promising results for setting the cut off for each of the five selected farm level criteria at the 50th percentile. Restricting testing to farms with a score ≥ 2 would have resulted in the same number of detected BVD positive farms as testing all farms, i.e., the outcome of the 2013 surveillance programme could have been reached with a smaller survey. CONCLUSIONS: The seasonality and time dependency of the activity of single farms in the networks requires a careful assessment of the actual time period included to determine farm level criteria. However, selecting farms in the sample for risk-based surveillance can be optimized with the proposed scoring system. The system was validated using data from the BVD eradication program. The proposed method is a promising framework for the selection of farms according to the risk of infection based on animal movements.