Every year there is some form of disease outbreak in swine herds across the US. Whether it is PRRSV, PEDV, or something else, we need to make sure that we are doing everything in our power to maintain a high health status on our farms. In this podcast Dr. Cesar Corzo talks with Laura Greiner about his work on his Swine Health Monitoring Program about ways we can minimize the spread of diseases to other farms, and how to more effectively keep our farms disease free.Continue reading “Disease surveillance programs: a podcast episode”
Our monthly collaboration with the National Hog Farmer continues; this month Dr. Kim VanderWaal shares her research regarding swine disease surveillance.
The multi-site pig production structure of the U.S. swine industry requires frequent movement of swine, making swine populations vulnerable to disease spread. This scenario becomes even more relevant in highly dense regions that concentrate thousands of pigs.
By targeting sites that play an important “connectivity” role such as gilt producing sites, prevention and control strategies for disease containment can be developed together with targeted surveillance for early detection of disease.
Swine movement data in three large production systems in the United States were analyzed to measure how a specific farm could influence a potential disease spread. Several network metrics were measured including:
- the number of other farms to which a specific farm sent or received pigs,
- the Mean Infection Potential (MIP), which measures potential incoming and outgoing infection chains.
For example, if a nursery farm received pigs from several sow farms and then sent pigs to multiple finisher farms, that farm would likely have a high MIP and could be called a “super-spreader” : a farm that could contribute to a high number of infections.
The study found that by directing disease interventions toward farms based on their MIP, the potential for infectious disease transmission in the production system can be substantially reduced. Interestingly, production type (sow, nursery, finishing, farrow-finish and wean-to-finish) did not seem to be a key determinant of the MIP.
When we really break it down, it’s all about incoming and outgoing contacts and the impact on risk. For more information about analysis of movement data, identifying super-spreaders farms and implications for disease control for farms in your system, contact Kim VanderWaal.