Farmscape for December 17, 2020
The Swine Health Information Center is planning to expand a project which uses machine learning to calculate when a sow farm will break with Porcine Epidemic Diarrhea.
Researchers with the University of Minnesota have built machine learning algorithms that consider factors such as recent animal movements, current disease distribution and environmental factors to predict whether a sow farm will break with PED two weeks in advance.
Swine Health Information Center Executive Director Dr. Paul Sundberg explains, while the swine sector better understands the epidemiology of Porcine Epidemic Diarrhea virus and Porcine Reproductive and Respiratory Syndrome virus, the ability of producers to effectively estimate the risk of disease outbreak risk has been lacking.
Clip-Dr. Paul Sundberg-Swine Health Information Center:
If we can predict for example an outbreak of PED on a farm two weeks before it would happen then you've got to think about the opportunity for being able to ramp up biosecurity or ramp up management, maybe early weaning or other things that could happen on that farm to prevent or to proactively respond to a predicted outbreak.
The issue here is not to dry wolf and say oh my gosh something's going to happen and then it never does.
The issue is to get this whole program as effective as possible, as targeted as possible and as efficient as possible to be able to accurately predict an outbreak of PED so we have confidence that it's going to happen.
We're making good steps toward that goal and I think we're almost there.
We’re going to get to that goal and when we get there, I'm really looking forward to applying it to other diseases.
We may be able to apply it to PRRS for example which would be a major step in PRRS control and PRRS management.
More information on University of Minnesota swine disease forecasting tool can be found at swinehealth.org.
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