An approximately 48 million people experience foodborne illnesses in the United States each year, however, only a small proportion of cases are captured by traditional surveillance systems. This is mainly due to a limited number of affected persons seeking medical care and reporting symptoms to appropriate authorities. We therefore aim to supplement existing surveillance systems by developing a validated system for monitoring reports of foodborne illnesses using event-based digital disease surveillance data sources, and characterize and estimate the extent of foodborne illnesses and disease outbreaks in the United States. Specifically, we aim to marry recent technologies for automated, disease outbreak detection with social media and online restaurant and food service review sites in order to comprehensively assess the extent of foodborne illnesses at a local and national scale. Building on our previous experience in digital disease detection from developing HealthMap.org, a leading global disease monitoring system, we will first identify and develop a corpus of relevant event-based infectious disease surveillance data sources for tracking foodborne illnesses. We will expand on HealthMap's data sources by incorporating data from social media, blogs, local news sources, restaurant and food service review sites. Next, we would validate the use of the event- based infectious disease surveillance data sources identified for tracking spatiotemporal trends in reports of foodborne illnesses. We would use regression models to quantitatively compare the event- based informal data sources to formal reporting from the various surveillance systems available through the U.S. Centers for Disease Control and Prevention (CDC). This will allow us to understand the biases inherent in our surveillance approach and to correct for them. Lastly, using a multiplicative model, we would determine the extent of foodborne illnesses and disease outbreaks at the local and national level. We will determine whether there are changes in overall rates of foodborne illness and disease reports locally and nationally. We would also extract data on foods and venues typically implicated in foodborne illnesses and diseases outbreaks to estimate the prevalence and incidence of foodborne illness through specific food vehicles and locations. Guided by our advisers at the CDC and local public health departments, we plan to present an approach that would help to improve surveillance of foodborne illnesses and disease outbreaks by providing a system for rapid assessment of foodborne illness at the local and national level.

Public Health Relevance

Although there have been several regulations and initiatives to improve food safety and surveillance of foodborne diseases, foodborne illnesses continue to remain a major public health problem in the United States. Our ability to respond and limit the spread of foodborne disease outbreaks and to improve food safety depends on our ability to properly understand the extent of foodborne illnesses at the local and national level. Our goal is therefore to develop and make available a new approach that allows for the assessment, validation and integration of multiple data sources for monitoring and estimating the extent of foodborne illnesses at the local and national scale.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Research Project (R01)
Project #
5R01LM011965-02
Application #
9062505
Study Section
Biomedical Library and Informatics Review Committee (BLR)
Program Officer
Sim, Hua-Chuan
Project Start
2015-05-01
Project End
2018-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Children's Hospital Boston
Department
Type
DUNS #
076593722
City
Boston
State
MA
Country
United States
Zip Code
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