The Swine Health Information Center’s (SHIC) November Domestic Swine Disease Monitoring Report is available. This month’s Domestic Swine Disease Monitoring Report shows a moderate increase in case positivity for porcine reproductive and respiratory syndrome virus (PRRSV), mostly contributed by a substantial increase in detection from wean-to-market animals. The October detection levels for porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and Mycoplasma hyopneumoniae were similar from September. At a state level, PRRSV detection was three standard deviations above expected in Minnesota, Iowa, South Dakota, Nebraska, Missouri, Illinois, and Indiana. In the podcast, the SDRS hosts talk with Dr. Tara Donovan about her experiences in leveraging veterinary diagnostic and swine production information to support data-driven decisions to improve further the health, welfare, and productivity of swine populations.
View the full report dashboards and listen to podcasts in the online portal. No login required.
What is the Swine Disease Reporting System (SDRS)?
SHIC-funded, veterinary diagnostic laboratories (VDLs) collaborative project, with goal to aggregate swine diagnostic data from participating reporting VDLs, and report in an intuitive format (web dashboards), describing dynamics of disease detection by pathogen or disease syndrome over time, specimen, age group, and geographical space. For this report, data is from the Iowa State University VDL and South Dakota State University ADRDL. University of Minnesota VDL and Kansas State University VDL. Specifically, for PRRSV RFLP data, and syndromic information the results are from Iowa State University VDL. For all "2019 predictive graphs," the expected value was calculated using a statistical model that considers the results from three previous years. The intent of the model is not to compare the recent data (2019) to individual weeks of previous years. The intent is to estimate expected levels of percent positive cases based on patterns observed in the past data, and define if observed percentage positive values are above or below the expected based on historic trends.