The Rapid Access Biosecurity (RAB) app standardizes Secure Pork Supply (SPS) biosecurity plans and creates maps to visualize the biosecurity infrastructure of individual farms across multiple states. In each state, the RABapp provides the pork producer and Department of Agriculture with rapid access to approved biosecurity plans status to expedite outbreak responses. For more information about SPS Secure Pork Supply please visit the SPS website.
At the NC State College of Veterinary Medicine, the Machado Lab is working with pork producers, state veterinary health officials and practitioners to ensure all stakeholders have rapid access to critical, enhanced SPS biosecurity plans.
Our Mission: Before foreign animal diseases (FADs) are introduced into disease-free countries such as the U.S., it is vital to catalogue and review biosecurity measures from individual farms throughout the swine industry, prioritize effective biosecurity measures, and integrate this information with animal movement data in a readily accessible and manageable user-friendly database. The RABapp database provides rapid access to the status of farm biosecurity plans and helps regulatory agencies harmonize effective response and recovery strategies.
Data Sources: All data sources used for the RABapp project are confidential and individual swine producers and pig-producing companies retain data ownership.
Team Members: The Machado Lab belong to the Department of Population Health and Pathobiology in the NC State College of Medicine. The team is working to prepare for and combat endemic swine diseases and help states nationwide build capacity for responding effectively to major biological threats and protecting the U.S. food supply. Contributors include:
- Jason A. Galvis, Ph.D.
- Nicolas C. Cardenas, Ph.D.
- Abagael Sykes, MSc.
- Kelsey Mills
- Madison Joyce
- Allyson Freeman
- Grace Winesett
- Gustavo Machado, Ph.D.
Disclaimer: All data used to develop the maps in the RABapp are visible only to authorized staff, veterinarians and state officials. This project has been supported by the Machado lab funds.