Transboundary diseases, including African swine fever (ASF), pose a significant threat to US pork producers. “We know early detection is the key to their control and elimination. But we also 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,” remarked Dr. Jeffrey Zimmerman, Iowa State University. “We need a new surveillance plan – something effective, yet practical and affordable.” Dr. Zimmerman and colleagues at Iowa State University conducted research funded by the Swine Health Information Center (SHIC) and the National Pork Board and found that “spatially balanced sampling” could achieve a higher probability of detection and at lower cost than previous methods.
Dr. Zimmerman says spatially balanced surveillance uses 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. “The results have been very promising in terms of developing a better approach for disease surveillance,” he commented. “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 their work, five spatially balanced sampling methods were compared 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 6000 farms, four of the five spatially balanced sampling methods provided better performance than random sampling. That is, for any given probability of detection, spatially balanced methods required testing fewer farms than SRS.
In an era of pandemics, 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 US, the USDA Center for Epidemiology and Animal Health in Fort Collins, Colorado, is developing surveillance methods for control areas, for example, determining how best to sample the farm or the 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.
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. The better performance and higher efficiency of spatially balanced sampling methods suggests a real improvement in regional livestock disease surveillance and the challenge of affordable surveillance. Future work will 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.
As the world deals with the COVID-19 pandemic, SHIC continues to focus efforts on prevention, preparedness, and response to novel and emerging swine disease for the benefit of US swine health. As a conduit of information and research, SHIC encourages sharing of its publications and research. Forward, reprint, and quote SHIC material freely. SHIC is funded by America’s pork producers to fulfill its mission to protect and enhance the health of the US swine herd. For more information, visit http://www.swinehealth.org or contact Dr. Sundberg at firstname.lastname@example.org.