A Digital Platform for Local Foodborne Illness and Outbreak Surveillance
PDF

How to Cite

Hawkins, J. B., Tuli, G., Kluberg, S., Harris, J., Brownstein, J. S., & Nsoesie, E. (2016). A Digital Platform for Local Foodborne Illness and Outbreak Surveillance. Online Journal of Public Health Informatics, 8(1). https://doi.org/10.5210/ojphi.v8i1.6474

Abstract

Foodborne illness affects 1 in 4 Americans, annually. However, only a fraction of affected individuals seek medical attention. In this presentation, we will discuss our collaboration with local public health departments to develop a foodborne disease surveillance platform to supplement ongoing surveillance efforts. The platform currently uses digital data from Twitter and Yelp. We developed a machine learning classifier to differentiate between relevant and irrelevant data. The classifier had an accuracy and precision of 85% and 82%, respectively based on an evaluation using 6084 tweets. These performance results are promising, especially given the similarities between the data classes.

https://doi.org/10.5210/ojphi.v8i1.6474
PDF
Authors own copyright of their articles appearing in the Online Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes. Share-alike: when posting copies or adaptations of the work, release the work under the same license as the original. For any other use of articles, please contact the copyright owner. The journal/publisher is not responsible for subsequent uses of the work, including uses infringing the above license. It is the author's responsibility to bring an infringement action if so desired by the author.