Transboundary diseases, including African swine fever (ASF), pose a significant threat to the U.S. pork industry. Early detection is critical to control and eliminate these diseases. Jeff Zimmerman, DVM and professor at Iowa State University, says it’s time for a new approach to detect transboundary diseases.
“We know that the approach that served the industry 30 years ago cannot keep pace with today’s big, fast industry, and the 5.2 million pigs that cross state lines each month,” Zimmerman says. “We need a new surveillance plan – something effective, yet practical and affordable.”
Zimmerman and colleagues at Iowa State University conducted research funded by the Swine Health Information Center (SHIC) and the National Pork Board and discovered that “spatially balanced sampling” could achieve a higher probability of detection and at lower cost than previous methods.
Spatially balanced surveillance compares a few samples from many farms across a defined region to determine the region’s status. In contrast, past methods tried to prove that each site was negative to prove a region as negative, he explains.
“The results have been very promising in terms of developing a better approach for disease surveillance,” Zimmerman says in a recent SHIC report. “Work currently in progress by our research team will continue to explore the strength of the approach and its potential to serve the swine industry.”
In the study, researchers compared five spatially balanced sampling methods to simple random sampling (SRS) in terms of the probability of detection by sample size. Using a livestock disease transmission model in a hypothetical region roughly the size of Iowa and populated with 6,000 farms, four of the five spatially balanced sampling methods provided better performance than random sampling, Zimmerman says.
For any given probability of detection, spatially balanced methods required testing fewer farms than SRS. In an era of pandemics, this is even more important. Active regional surveillance for early detection of emerging swine pathogens becomes urgent, yet shrinking budgets impose constraints.
To prepare for the introduction of ASF into the U.S., the USDA Center for Epidemiology and Animal Health in Fort Collins, Colo., is creating surveillance methods for control areas. For example, what is the best way to sample a farm or a population in a barn to verify the farm’s or barn’s disease status?
Outside of control areas, spatially balanced surveillance will be critical in verifying freedom from disease and supporting business continuity, he explains. Surveillance efficiency – achieving highest probability of detection at the lowest cost – is central to the public good.
This project represents the first step in the investigation of the use of spatially balanced sampling methods in regional livestock disease surveillance programs, Zimmerman says. The better performance and higher efficiency of spatially balanced sampling methods suggests a notable improvement in regional livestock disease surveillance and the challenge of affordable surveillance.
In the future, researchers plan to examine the impact of the rate of disease spread and the threshold distance for farm-to-farm transmission on the performance of spatially balanced sampling methods.
Zimmerman’s study, “Active Regional Surveillance for Early Detection of Exotic/Emerging Pathogens of Swine: A Comparison of Statistical Methods for Farm Selection,” was published in Preventive Veterinary Medicine.
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