Not that long ago, a group of US veterinary diagnosticians recognized the potential of being able to analyse “Big Data”. In this case the big data was the information generated from thousands of samples from diverse populations of animals submitted to veterinary diagnostic laboratories (VDLs) for testing on a daily basis. The problem, however, was that each VDL had its own laboratory information management system (LIMS), with processes and procedures to capture submission information, perform laboratory tests, define the boundaries of test results (i.e., positive or negative), and report results. These diagnosticians developed a Big Hairy Audatious Goal the envisioned data analysis platforms that would allow geographically disperse VDLs to exchange and share portions of laboratory data using standardized, reliable, and sustainable information technology processes. The concept was pitched and there was general buy in to the potential benefits.
Today, this collaborative approach to analysing diagnostic information is beginning to bear fruit. Recently, the system was used to standardize and aggregate data from swine submissions to multiple VDLs to detect in order to monitor porcine enteric coronaviruses by RT-PCR. Oral fluids, feces, and fecal swabs were the specimens submitted most frequently for enteric coronavirus testing. Statistical algorithms were used successfully to scan and monitor the overall and state-specific percentage of positive submissions. The major findings of this particular project included the following:
- customized messaging to allow inter-VDL exchange of information was effective
- a consistently recurrent seasonal pattern, with the highest percentage of positive submissions detected during December-February for porcine epidemic diarrhea virus, porcine deltacoronavirus, and transmissible gastroenteritis virus (TGEV).
- after 2014 there were very few submissions that tested positive for TGEV.
Take Home Information:
- Monitoring aggregated Veterinary Diagnostic Laboratory data proactively can allow for early detection of disease and then alert stakeholders early of significant changes.
- This improved system can also be used for surveillance of transboundary disease and can help to support a claim of negative status
- Kudos to these diagnosticians for having “dreamed the dream” and then went out and made it happen.
Ref: Giovani Trevisan , Leticia C M Linhares , Kent J Schwartz , Eric R Burrough , Edison de S Magalhães , Bret Crim , Poonam Dubey , Rodger G Main , Phillip Gauger, Mary Thurn , Paulo T F Lages , Cesar A Corzo , Jerry Torrison , Jamie Henningson , Eric Herrman , Rob McGaughey , Giselle Cino , Jon Greseth , Travis Clement , Jane Christopher-Hennings , Daniel C L Linhares J Vet Diagn Invest . 2021 Mar 19;10406387211002163. doi: 10.1177/10406387211002163. Online ahead of print.
