We developed a model to predict the cyclic pattern of porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection by reverse-transcription real-time PCR (RT-rtPCR) from 4 major swine-centric veterinary diagnostic laboratories (VDLs) in the United States and to use historical data to forecast the upcoming year’s weekly percentage of positive submissions and issue outbreak signals when the pattern of detection was not as expected. Standardized submission data and test results were used. Historical data (2015–2017) composed of the weekly percentage of PCR-positive submissions were used to fit a cyclic robust regression model. The findings were used to forecast the expected weekly percentage of PCR-positive submissions, with a 95% confidence interval (CI), for 2018. During 2018, the proportion of PRRSV-positive submissions crossed 95% CI boundaries at week 2, 14–25, and 48. The relatively higher detection on week 2 and 48 were mostly from submissions containing samples from wean-to-market pigs, and for week 14–25 originated mostly from samples from adult/sow farms. There was a recurring yearly pattern of detection, wherein an increased proportion of PRRSV RNA detection in submissions originating from wean-to-finish farms was followed by increased detection in samples from adult/sow farms. Results from the model described herein confirm the seasonal cyclic pattern of PRRSV detection using test results consolidated from 4 VDLs. Wave crests occurred consistently during winter, and wave troughs occurred consistently during the summer months. Our model was able to correctly identify statistically significant outbreak signals in PRRSV RNA detection at 3 instances during 2018.
Bibliographical noteFunding Information:
We thank VDL clients for submitting samples for testing. We also thank current and former SDRS advisory council members for their valuable input and volunteered time: Drs. Clayton Johnson, Emily Byers, Hans Rotto, Jeremy Pittman, Mark Schwartz, Paul Yeske, Pete Thomas, Rebecca Robbins, Tara Donovan, Matthew Turner, Deborah Murray, Scott Dee, and Melissa Hensch. This project was co-funded by the American Association of Swine Veterinarians Foundation award 018743-00001 and by the Swine Health Information Center (SHIC) awards 17-210 and 19-155 SHIC to D.C.L. Linhares.
This project was co-funded by the American Association of Swine Veterinarians Foundation award 018743-00001 and by the Swine Health Information Center (SHIC) awards 17-210 and 19-155 SHIC to D.C.L. Linhares.
© 2020 The Author(s).
- outbreak signal
- swine pathogens
- veterinary diagnostic laboratories
PubMed: MeSH publication types
- Journal Article