In this episode of The Swine Health Blackbelt Podcast, Dr. Tara Prezioso, a PhD candidate at the University of Illinois, explores how network modeling is improving disease prevention in the swine industry. She explains how movement data from farms, feed mills, and processing facilities can help predict and mitigate outbreaks like PEDV and ASF. Listen now on all major platforms!"By analyzing movement data, we can identify high-risk pathways for disease transmission and develop targeted prevention strategies."𝗠𝗲𝗲𝘁 𝘁𝗵𝗲 𝗴𝘂𝗲𝘀𝘁: Dr. Tara Prezioso is a PhD candidate in veterinary epidemiology at the University of Illinois Urbana-Champaign, with a DVM from North Carolina State University and an MPH. With 16 years of veterinary experience, she specializes in foreign animal disease prevention and statistical modeling in livestock systems. Her research focuses on using network modeling to predict and control disease outbreaks in swine populations.Click here to read the full research article!What you will learn:(00:00) Highlight(01:36) Introduction (02:58) Network modeling in swine (05:10) Movement data applications (07:36) PEDV data (09:27) Understanding average path length (12:36) Future research directions (14:30) Closing thoughtsThe Swine Health Blackbelt Podcast is trusted and supported by innovative companies like: Farm Health Guardian* Boehringer Ingelheim𝗟𝗶𝘀𝘁𝗲𝗻 𝗼𝗻 𝗔𝗽𝗽𝗹𝗲 𝗣𝗼𝗱𝗰𝗮𝘀𝘁𝘀, 𝗦𝗽𝗼𝘁𝗶𝗳𝘆 𝗼𝗿 𝗮𝗻𝘆 𝗺𝗮𝗷𝗼𝗿 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺.Website: The Swine Health Blackbelt PodcastInstagram: Swine CampusLinkedIn: Swine Campus

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