In the fluid and somewhat amorphous would of food supply chains, it can be difficult to trace a source of contamination in the event of a pathogen outbreak.

A new analysis developed by the Sandia National Laboratories’ National Infrastructure Simulation and Analysis Center (NISAC) could make this vital detective work much more accurate and efficient.

According to the center’s report published in the International Journal of Critical Infrastructures, a probability map along with a method called ‘stochastic network representation’ will help epidemiologists in their analyses.

“Stochastic network representation provides the ability to incorporate and express the uncertainties using probability maps,” Sandia analyst Stephen Conrad explained. “The method enables effective risk analysis and designing robust food defense strategies.”

Currently, epidemiologists must interview affected people, suppliers and buyers when a foodborne pathogen outbreak occurs. These interviews can often take place after the exposure has run its course and any possibly contaminated food has been completely recalled. This reactive policy is susceptible to inaccurate, outdated, and incomplete information, making it difficult to identify a food culprit.

“Epidemiologists involved in trace back start behind the eight ball,” Conrad said. “They attempt to reconstruct the pathway the contaminated food has traveled through the distribution network well after the fact.”

After the likely culprit has been identified, epidemiologists trace along the distribution chain to locate the source of contamination.

The contemporary process can be quite daunting as supply chains can vary widely from region to region and country to country. In addition, the supply chain is constantly in flux as a result of market pressures. According to a statement from Sandia, even many supply chain insiders don’t understand the breadth of their network and “know only their direct supplier and direct customer.”

To test their new methods, Sandia applied the stochastic mapping technique on the fresh sprout sector in a single U.S. state, a decision influenced by the E. coli outbreak that affected parts of Europe in 2011 and proved difficult to trace.

“The case study demonstrates how mapping the network topology and modeling the potential relationships allows users to determine the likely contaminant pathways and sources of contamination,” the journal report said.

According to the center, future studies will concentrate on scaling up to the technique to the level of an entire industry. The center also plans to work with business and governmental organizations to determine who could benefit from the new methodology.

“If stochastic mapping was widely used now, perhaps outbreaks, such the recent ones involving salmonella, could be more quickly tracked down and contained. Quicker containment would benefit not only consumers but also the farmers who grow fresh food for our nation and who can be severely impacted economically by uncertainties and market restrictions on sales of their products caused by delays in pinpointing an outbreak’s source,” Conrad said.

The methods developed by NISAC are the result of four years of research that was funded by Sandia’s Laboratory Directed Research and Development program and the Department of Homeland Security, according to the center’s press release.