In a new study, UKHSA researchers have assessed different types of AI for their ability to detect and classify text in online restaurant reviews, which could one day be used to identify and potentially target investigations into foodborne illness outbreaks.

Foodborne gastrointestinal (GI) illness is a major burden on society's health in the UK, causing millions of people to become unwell every year.

UKHSA researchers looked at a range of large language models and rated their ability to trawl thousands of online reviews for information about symptoms that might relate to GI illness and the different food types people report eating.

They believe that gathering information in this way could one day become routine, providing more information on rates of GI illness that are not captured by current systems, as well as vital clues around possible sources and causes in outbreaks.

However, the study has highlighted key challenges around the approach that would need to be overcome first, particularly around access to real-time data.

In addition, determining which specific ingredients or other factors may be linked is difficult, variations in spelling and the use of slang were also identified as potential challenges, as well as people misattributing their illness to a given meal.

Professor Steven Riley, chief data officer at UKHSA, said: ‘Using AI in this way could soon help us identify the likely source of more foodborne illness outbreaks, in combination with traditional epidemiological methods, to prevent more people becoming sick.

‘Further work is needed before we adopt these methods into our routine approach to tackling foodborne illness outbreaks.'