Brief

How big data could speed up foodborne illness investigations

Dive Brief:

  • Researchers have found another way that big data could improve the food system: by speeding up investigations into foodborne illness outbreaks.
  • A computational technique enables researchers to either identify potential contamination sources when the outbreak is still in its early stages or make proactive predictions about likely contamination sources before an outbreak begins.
  • The data involved includes retail scanner data with spatial information collected from grocery stores and confirmed geocoded cases gathered from public health agencies' reports. Together, this data results in quick identification of a list of suspected products that researchers can investigate.

Dive Insight:

Speed is essential to reacting to instances of foodborne illness to minimize illness and loss, whether that's monetary, reputation or loss of life. Traditional methods like interviews and surveys still play an important role in investigations, but they can be time and labor-intensive and invite opportunity for human error. Big data can make the process faster, easier and more accurate for all parties involved, which could save time and money.

With this algorithm, manufacturers and public health agencies could reduce the time it takes to narrow down a list of potential contamination sources from days or weeks to hours based on as few as 10 medical examination reports for a foodborne illness. Having a more accurate list in a short period of time can give manufacturers more breathing room to plan how best to approach a recall, if necessary, and any changes they need to make to their operations to fix the problem and prevent it from recurring.

The sooner agencies and manufacturers can identify the product and specific lot and batch numbers, the faster they can alert consumers and pull those products — and any other products that use the contaminated product as an ingredient — off the market. Having additional data can also help manufacturers be more transparent about a recall or foodborne illness outbreak linked to their products because they can pass some of that data along to consumers.

Big data could also be critical for cases where investigators could never clearly identify a contamination source, such as the CRF Frozen Foods recall and listeria contamination that impacted more than 350 frozen food products under 42 brand names earlier this year.

Filed Under: Food Safety