Equine syndromic surveillance in Colorado using veterinary laboratory testing order data.
Authors: Burkom Howard, Estberg Leah, Akkina Judy, Elbert Yevgeniy, Zepeda Cynthia, Baszler Tracy
Journal: PloS one
Summary
# Editorial Summary: Equine Syndromic Surveillance in Colorado The US Department of Agriculture's Risk Identification Unit has developed a novel surveillance system using veterinary laboratory testing data to detect emerging health threats in horses, marking a significant shift from traditional passive reporting towards real-time syndromic monitoring. Working with Colorado State University laboratories and statistical experts, researchers analysed 12 years of equine test records to construct syndrome groupings that reflect clinically meaningful disease clusters whilst avoiding false alerts generated by routine testing patterns. Key findings demonstrated that raw laboratory test order data required substantial refinement through consultation with laboratory staff and stakeholder input to create actionable surveillance categories—a process that revealed the critical importance of understanding local laboratory workflows and testing biases. The team developed customised statistical detection methods tailored to the characteristics of equine diseases and laboratory data structures, rather than applying generic surveillance algorithms. For equine professionals, this work underpins an emerging early-warning system that could identify unusual disease patterns weeks or months before traditional reporting mechanisms; participation in such surveillance initiatives through accurate record-keeping and communication with diagnostic laboratories strengthens the profession's collective ability to respond quickly to emerging health challenges.
Read the full abstract on PubMed
Practical Takeaways
- •Veterinary practitioners can benefit from knowing that passive surveillance systems based on routine lab testing provide valuable early warning signals for emerging equine health issues in their region.
- •Laboratory test ordering patterns are being systematically analyzed to detect disease clusters before they become widespread clinical problems—awareness of this surveillance may help practitioners recognize their role in disease detection.
- •This infrastructure enables more rapid response to novel disease threats or unusual case clusters through coordinated epidemiological monitoring at the state and national level.
Key Findings
- •A syndromic surveillance system was developed using 12 years of equine laboratory test order data from three state laboratories in Colorado to enable early detection of disease patterns.
- •Trial syndrome groups were created based on RIU experience and published literature, then refined through exploratory analysis and stakeholder consultation to reduce false alerting.
- •The system required customized statistical detection methods tailored to laboratory information characteristics and disease epidemiology to effectively monitor equine health.