Combining technology and animal health, a group of Kansas State University researchers is developing a more effective way to predict the spread of foot-and-mouth disease and the impact of preventative measures.
The researchers are finding that if a foot-and-mouth disease outbreak is not in the epidemic stage, preemptive vaccination is a minimally expensive way to halt the disease's spread across a network of animals. But if there's a high probability of infection, computer models show that culling strategies are better.
"We are trying to do predictive as well as preventative modeling using a network-based approach," said Sohini Roy Chowdhury, a master's student in electrical engineering. "First we track how the infection is spreading in space and time. Then we try to mitigate that with certain strategies. The novel contribution of this project is that we considered networks in countries like Turkey, Iran and Thailand that don't have a highly built database."
Roy Chowdhury is working with Caterina Scoglio, associate professor of electrical and computer engineering, and William Hsu, associate professor of computing and information sciences. They presented the work in December 2009 at the Second International Conference on Infectious Diseases Dynamics in Athens, Greece.
The researchers used mathematical equations to predict how foot-and-mouth disease spreads over a network of infected herds. In the network, the nodes are places like stockyards and grazing lands where animals are held. They are connected in various ways, such as by animals' grazing movements and by how people and vehicles move among the herds. Hsu said the researchers' goal is to increase the accuracy of models that predict disease spread in these networks over space and time.
In the experiments, the researchers ran up to a week of predictive modeling on a real network and saw how well it matched data from the actual episode. Roy Chowdhury said they also
|Contact: Caterina Scoglio|
Kansas State University