Swine Global Surveillance Project Issues First Reports

cahfs_primary_graphicThe University of Minnesota Swine Group and the Center for Animal Health and Food Safety (CAHFS) have partnered with the Swine Health Information Center (SHIC) to develop and implement a system for near real time global surveillance of swine diseases. The output of the system is the identification of hazards that are subsequently scored using a step-wise procedure of screening, to identify increments in hazards that, potentially, may represent a risk for the US.

The first version of the system is now live, with the first three reports available, including data from November 5, 2017 to January 14, 2018.

Beginning in early March the tool will be available for spontaneous reporting by stakeholders, such as producers and practitioners both overseas and in the United States. During the first year of the project, the system will be developed and beta-tested for USDA-classified tier 1 reportable foreign animal swine diseases (ASF, CSF, FMD), but in the future more diseases will be tracked.

“As we have learned in recent years, we need to pay attention to external health threats as part of our overall risk management. Keeping tabs on global trends is a prudent investment,” said Dr. Jerry Torrison, Director of the University of Minnesota Veterinary Diagnostic Laboratory.

From the most recent report, December 18, 2017 – January 14, 2018:

The current concern continues to focus on African swine fever in Poland and surrounding countries. Infected wild boars continue to be identified in the vicinity surrounding Warsaw, and the possibility of spread of the disease to the pig intensive area of eastern Poland continues to be a concern. Countries in the region are using a combination of increased hunting of wild boar along with boar proof fencing along borders to attempt to control the spread of the disease.

Visit z.umn.edu/SwineGlobalSurveillance to access the reports, and coming soon, to use the tool to provide spontaneous reporting.

Science page: How farm structure and demography impact disease detection

This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.

This week’s edition reports the latest research on modeling the spread of swine vesicular diseases based on farm structure and number of sites. The model was then used to establish an expected time to detection. Two virus strains (high versus low virulence) were evaluated with the model to assess how the strain would influence the time to detection in a farm.

Key points from this week edition:

  • The models showed that the virus persisted longer in farms with a farrowing unit.
  • It is more difficult to diagnose FMD when the strains cause low mortality or no mortality.

Click on the link to see the details about disease spread models.


Defining parameters to develop epidemiological models of a Foot and Mouth Disease incursion: meta-analysis of the disease biology


Models are primordial to develop the best control and eradication measures as well as to decrease response time in the event of a Foot and Mouth Disease (FMD) incursion on US soil. However, to be as representative of real-life situation as possible, these models need the most accurate information on disease biology. This scientific article, written by a U of M team of epidemiologists: Drs. Kinsley, Patterson, VanderWaal, Craft, and Perez, is a meta-analysis of the peer-reviewed literature defining what the exact values for the duration of various disease periods such as: latency, incubation and sub-clinical phases are. The total duration of infection is also examined.

Time course of a FMD infection in pigs infected through contact with an inoculated pig.

Abstract: In the event of a foot-and-mouth disease (FMD) incursion, response strategies are required to control, contain, and eradicate the pathogen as efficiently as possible. Infectious disease simulation models are widely used tools that mimic disease dispersion in a population and that can be useful in the design and support of prevention and mitigation activities. However, there are often gaps in evidence-based research to supply models with quantities that are necessary to accurately reflect the system of interest. The objective of this study was to quantify values associated with the duration of the stages of FMD infection (latent period, subclinical period, incubation period, and duration of infection), probability of transmission (within-herd and between-herd via spatial spread), and diagnosis of a vesicular disease within a herd using a meta-analysis of the peer-reviewed literature and expert opinion. The latent period ranged from 1 to 7 days and incubation period ranged from 1 to 9 days; both were influenced by strain. In contrast, the subclinical period ranged from 0 to 6 days and was influenced by sampling method only. The duration of infection ranged from 1 to 10 days. The probability of spatial spread between an infected and fully susceptible swine farm was estimated as greatest within 5 km of the infected farm, highlighting the importance of possible long-range transmission through the movement of infected animals. Finally, while most swine practitioners are confident in their ability to detect a vesicular disease in an average sized swine herd, a small proportion expect that up to half of the herd would need to show clinical signs before detection via passive surveillance would occur. The results of this study will be useful in within- and between-herd simulation models to develop efficient response strategies in the event an FMD in swine populations of disease-free countries or regions.

Link to the full article

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