Prediction of seasonal patterns of porcine reproductive and respiratory syndrome virus RNA detection in the U.S. swine industry
| العنوان: | Prediction of seasonal patterns of porcine reproductive and respiratory syndrome virus RNA detection in the U.S. swine industry |
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| المؤلفون: | Paul Sundberg, Mary Thurn, Chong Wang, Jerry Torrison, Paulo Lages, Bret Crim, Poonam Dubey, Douglas Marthaler, Jamie Henningson, Daniel Linhares, Jane Christopher-Hennings, Giovani Trevisan, David Muscatello, Rodger Main, Leticia Linhares, Gregg Hanzlicek, Eric R. Burrough, Eric Herrman, Kent Schwartz, Jon Greseth, Cesar Corzo, Ram K. Raghavan, Travis Clement |
| المصدر: | J Vet Diagn Invest |
| بيانات النشر: | SAGE Publications, 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | 0303 health sciences, Veterinary medicine, General Veterinary, Swine, 040301 veterinary sciences, animal diseases, Porcine Reproductive and Respiratory Syndrome, Outbreak, RNA, 04 agricultural and veterinary sciences, Biology, Porcine reproductive and respiratory syndrome virus, biology.organism_classification, Polymerase Chain Reaction, United States, Confidence interval, Disease Outbreaks, 0403 veterinary science, 03 medical and health sciences, Animals, RNA, Viral, Porcine respiratory and reproductive syndrome virus, Seasons, Full Scientific Reports, 030304 developmental biology |
| الوصف: | 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. |
| تدمد: | 1943-4936 1040-6387 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f95429f30cf85a102f92ab7aea5be6c9 https://doi.org/10.1177/1040638720912406 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....f95429f30cf85a102f92ab7aea5be6c9 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 19434936 10406387 |
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