December Domestic Swine Disease Monitoring Report Now Available
December 4, 2019 —
The Swine Health Information Center's (SHIC) December Domestic Swine Disease Monitoring Report is available.
In the December report, the percentage of positive porcine reproductive and respiratory syndromve virus (PRRSV) cases in November was 26.15%, up from 22.65% in October, with increased detection in all age categories. The increase follows the predicted expectation for the period. Porcine epidemic diarrhea virus (PEDV) overall positive cases in November were at 13.97%, up from 10.82% in October. The increased detection of PEDV RNA was above expected, mostly driven by wean-to-market animals. The overall porcine deltacorona virus (PDCoV) percentage of positive cases in November was at 4.18%, up from 2.13% in October. There was a signal for increased detection of M. hyopneumoniae above expected in November. Details on these and other monitoring results are included in the full report.
View the full report dashboards 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.
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