A novel approach to predicting disease risk will be developed and tested in a newly funded Swine Health Information Center (SHIC) project. Once the process is tested and verified, this innovative project will give producers and practitioners the opportunity to use their data to predict a change in disease risk that could lead to an outbreak. Armed with this information, they may be able to proactively prevent an outbreak or at least decrease its impact.
The University of Minnesota project could be the next evolutionary step for using data to affect animal health and disease outbreaks. The novel model will show how environmental, pig movement, neighbor disease status and other on-farm and neighborhood factors can help predict the risk of disease outbreaks. The model will then be applied to real world data so producers and their veterinarians can be aware and better prepared to prevent or respond.
This study will advance understanding of details affecting between-farm disease spread, including the relative importance of risk factors for sow farm breaks across time and space. Using already available PRRS/PED data to develop the model will bring a better understanding of how risk factors change across the landscape. It will help in managing those diseases as it is also developed for emerging diseases.
Project success will depend on the availability of the data. Cooperating producers and their practitioners are being identified and invited to participate. This project will also reinforce the value that can be achieved by sharing data and experiences across production systems and veterinary practices. The model will be developed, tested and verified before being applied to real-time data and reports produced.