A new system from IBM promises to help food retailers, distributors and public health officials accelerate foodborne disease outbreak investigations.
“Predictive analytics based on location, content, and context are driving our ability to quickly discover hidden patterns and relationships from diverse public health and retail data,” James Kaufman, manager of public health research for IBM Research said in the release. “We are working with our public health clients and with retailers in the U.S. to scale this research prototype and begin focusing on the 1.7 billion supermarket items sold each week in the U.S..”
Using algorithms, visualization, and statistical techniques, the tool can use information on the date and location of billions of supermarket food items sold each week to quickly identify with high probability a set of potentially “guilty” products with in as few as 10 outbreak case reports, according to the release.
The research relating to the subject was published in the journal PLOS Computational Biology together with collaborators from Johns Hopkins University, Purdue University and the German Federal Institute for Risk Assessment, according to the release.
IBM scientists worked with the Department of Biological Safety of the German Federal Institute for Risk Assessment, according to the release. In one demonstration, scientists simulated 60,000 outbreaks of foodborne disease across 600 products using real-world food sales data from Germany.
The success of the system depends on sharing of data between private business and public health officials, according to the release. If the relevant data would be provided by the retail companies, the speed of investigation could be improved substantially, according to the release.
“This research illustrates an approach to create significant improvements without the need for any regulatory changes,” Bernd Appel, head of the department biological safety for the German Federal Institute for Risk Assessment said in the release. “This can be achieved by combining innovative software technology with already existing data and the willingness to share this information in crisis situations between private and public sector organizations.”