Evaluating perspectives for PRRS virus elimination from pig dense areas with a risk factor based herd index

Porcine reproductive and respiratory syndrome virus (PRRSV) is wide-spread in pig populations globally. In many regions of Europe with intensive pig production and high herd densities, the virus is endemic and can cause disease and production losses. This fuels discussion about the feasibility and sustainability of virus elimination from larger geographic regions. The implementation of a program aiming at virus elimination for areas with high pig density is unprecedented and its potential success is unknown. The objective of this work was to approach pig population data with a simple method that could support assessing the feasibility of a sustainable regional PRRSV elimination. Based on known risk factors such as pig herd structure and neighborhood conditions, an index characterizing individual herds' potential for endemic virus circulation and reinfection was designed. This index was subsequently used to compare data of all pig herds in two regions with different pig- and herd-densities in Lower Saxony (North-West Germany) where PRRSV is endemic. Distribution of the indexed herds was displayed using GIS. Clusters of high herd index densities forming potential risk hot spots were identified which could represent key target areas for surveillance and biosecurity measures under a control program aimed at virus elimination. In an additional step, for the study region with the higher pig density (2463 pigs/km(2) farmland), the potential distribution of PRRSV-free and non-free herds during the implementation of a national control program aiming at national virus elimination was modeled. Complex herd and trade network structures suggest that PRRSV elimination in regions with intensive pig farming like that of middle Europe would have to involve legal regulation and be accompanied by important trade and animal movement restrictions. The proposed methodology of risk index mapping could be adapted to areas varying in size, herd structure and density. Interpreted in the regional context, this could help to classify the density of risk and to accordingly target resources and measures for elimination.

Demographic model of the Swiss cattle population for the years 2009-2011 stratified by gender, age and production type

Demographic composition and dynamics of animal and human populations are important determinants for the transmission dynamics of infectious disease and for the effect of infectious disease or environmental disasters on productivity. In many circumstances, demographic data are not available or of poor quality. Since 1999 Switzerland has been recording cattle movements, births, deaths and slaughter in an animal movement database (AMD). The data present in the AMD offers the opportunity for analysing and understanding the dynamic of the Swiss cattle population. A dynamic population model can serve as a building block for future disease transmission models and help policy makers in developing strategies regarding animal health, animal welfare, livestock management and productivity. The Swiss cattle population was therefore modelled using a system of ordinary differential equations. The model was stratified by production type (dairy or beef), age and gender (male and female calves: 0-1 year, heifers and young bulls: 1-2 years, cows and bulls: older than 2 years). The simulation of the Swiss cattle population reflects the observed pattern accurately. Parameters were optimized on the basis of the goodness-of-fit (using the Powell algorithm). The fitted rates were compared with calculated rates from the AMD and differed only marginally. This gives confidence in the fitted rates of parameters that are not directly deductible from the AMD (e.g. the proportion of calves that are moved from the dairy system to fattening plants).

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.