Online Program

Identifying Unreported FoodBorne Disease Using Social Media Data

Monday, November 2, 2015 : 10:30 a.m. - 11:30 a.m.

Raed Mansour, MS, Chicago Department of Public Health, City of Chicago, Chicago, IL

Jenine Harris, PhD, George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, MO
Vasudha Reddy, MPH, Bureau of Communicable Disease, New York City Dept of Health and Mental Hygiene, Queens, NY
Luis Gravano, PhD, Computer Science Department, Columbia University, New York City, NY
Noemie Elhadad, PhD, Department of Biomedical Informatics, Columbia University, New York City, NY
Jared Hawkins, PhD, Computational Epidemiology Group, Boston Children's Hospital, Harvard Medical School, Boston, MA
Kristal J. Southern, DVM, MPH, Public Health Informatics and Surveillance Applied Epidemiology Staff, USDA/FSIS/OPHS/AES, Washington, DC
Janet B. Stevens, PMP, Office of the Chief Information Officer Office of the Administrator, Food Safety and Inspection Service, USDA, Washington, DC
Crowd sourcing information via social networks, has been enormously successful for organizations and businesses. However, public health has rarely leveraged this data to protect and promote health, especially when related to food poisoning. The Centers for Disease Control and Prevention estimates about 48 million Americans develop a foodborne illness annually, resulting in over 128,000 hospitalizations and 3,000 deaths. The estimated economic impacts of these illnesses can be up to $77 billion per year. Most people do not report being food poisoned and it’s estimated that only 2.9% of those who do become food poisoned, seek medical care. The following agencies and organizations are researching and developing technological innovations to filter through social media data and leverage crowd sourcing to identify and respond to potential food poisoning cases that would historically go unreported, thereby better protecting the food supply and overall public health:
  • New York City Department of Health and Mental Hygiene and Columbia University;
  • Chicago Department of Public Health and Smart Chicago Collaborative;
  • Harvard Medical School and Boston Children's Hospital; and
  • United States Department of Agriculture Food Safety Inspection Service.

Learning Areas:

Communication and informatics
Other professions or practice related to public health

Learning Objectives:
Discuss syndromic surveillance through the lens of non-traditional data in social media. Identify non-traditional data sources for developing models to discover potential food safety risks. Demonstrate models of infodemiology and infoveillance using social media for food safety. Explain how machine learning and predictive analytics can be integrated within traditional food protection practices to prevent food poisoning. Explain how to design strategies for innovations in data science and social media within existing policies. Demonstrate how to build public health capacity and sustainability through multidisciplinary collaboration with partners for food safety in public health.

Keyword(s): Social Media, Food Safety

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am currently advise on a grant to assist in technology that I helped implement for the Chicago Department of Public Health's FoodBorne Chicago application for food safety.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.