Foodborne disease has emerged as a serious and underreported public health problem with high health and financial costs. The World Health Organization (WHO) identifies foodborne illness outbreaks as a major global public health threat in the twenty-first century. Traditional surveillance systems such as Canadian Notifiable Disease Surveillance System capture only a fraction of the estimated 4 million annual cases of foodborne illness in Canada. They rely on the collection of numerous indicators including clinical symptoms, virology laboratory results, hospital admissions and mortality statistics resulting in a median delay of 6.5 days between case report from clinicians to the health departments. Public health decision-makers consider the delayed notification as a barrier to investigating foodborne disease, as it can potentially distribute geographically across great distances. Early detection of foodborne disease can reduce the number of exposed individuals by removing contaminated product from retail and foodservice outlets, increasing public awareness, and offering a more timely preventative and therapeutic measures to exposed individuals. We propose that social media data should be exploited as a complementary component of the traditional surveillance systems. The enormity and high variance of the information that propagates through large user communities presents the opportunity to mine the data for signals of foodborne disease activity; analyze illness patterns qualitatively and quantitatively; and to predict future outbreaks. We propose a host of social media-based predictive models to characterize and detect upcoming foodborne illness outbreaks through ambient tracking and monitoring over users’ conversations in social media. The objective is to advance research on foodborne disease detection from non-traditional sources to supply health decision makers with situational awareness.

Industry Partner(s):AdaptCore Technologies Inc.

Academic Institution:Ryerson University

Academic Researcher: Ebrahim Bagheri

Focus Areas: Digital Media, Health

Platforms: Cloud