Performing Department
VETERINARY DIAGNOSTIC AND PRODUCTION ANIMAL MEDICINE - CVM
Non Technical Summary
Infectious disease outbreaks continue to threaten the health & productivity of the US swine herd. The severity and magnitude of disease impact depend on the interaction of herd characteristics and practices implemented in response to outbreaks. Even though veterinarians and producers record aspects related to disease outbreak response & recovery, this data is often stored in disconnected databases, hampering the ability to exchange knowledge, experiences, and data-driven discussions in the swine industry.We will leverage the combined experience of the working team to assemble a cyberinfrastructure platform to store and aggregate data from herds experiencing disease outbreaks with PRRS virus, the most economically significant pathogen affecting the US swine herd. The model, which can later be adapted to other pathogens and food animal species, will reveal and benchmark aspects related to response & recovery from outbreaks. Benchmarking efforts will facilitate discussions with veterinarians, producers, and industry partners that offer relevant products or technology to respond to diseases. Regression and artificial intelligence-based analyses will forecast recovery parameters, provide a recovery prognosis, and provide producer-specific decision trees on best practices for swifter recovery from outbreaks.Strategic collaborations and extension activities will foster the Precision Disease Management concept. Activities will promote the implementation of strategies and field-applied knowledge to support producers in making data-driven decisions to efficiently improve response & recovery from outbreaks. The integrated project will significantly improve the health & productivity of the US swine herd, creating the capacity to manage existing and future endemic and emerging infectious disease threats.
Animal Health Component
75%
Research Effort Categories
Basic
25%
Applied
75%
Developmental
0%
Goals / Objectives
The overall objective is to develop and implement a disease intelligence platform to capture, benchmark, analyze, and forecast standardized aspects related to the recovery of swine populations following disease outbreaks.
Project Methods
For the research goals, this project will develop and launch a secure, sustainable, and scalable digital platform to store standardized key metrics about the onset, response, and recovery of outbreaks. The consolidated data will be used to reveal the characteristics of swine herds experiencing PRRSV outbreaks in the US, benchmark health interventions, biosecurity, and bio-management practices implemented in response to outbreaks, and provide forecasting and prognosis of key recovery metrics to herds. Generated information will be used in the decision-making process to support veterinarians and producers to effectively employ data-driven solutions to timely respond to outbreaks. Data analyses will be performed on the project's secure data warehouse that will capture and organize standardized health, productivity, demographics, interventions, and practices related to disease outbreaks in swine populations.Regarding extension, the overall goal is to bridge the gap between academia and the broader swine community in achieving a rapid, effective, and data-driven response(s) to disease outbreaks affecting the US swine herd. The plan will be accomplished by consistent data sharing, communication of research findings, feedback collection with practicing veterinarians and producers, and ongoing benchmarking of the aspects associated with disease outbreaks. An advisory council will be established, including veterinarians, epidemiologists, and small and large swine producers. The group will discuss findings, fine-tune the research goals, assess opportunities for allocation of resources and interventions, and broadly promote the concept and disseminate knowledge from the research goals. The integrated field-based research & extension initiatives will improve the capacity for disease response in the US swine herd.