Abstract
We discuss our efforts in detection and tracking using Twitter data collected from January 2013 to the present and discuss various issues that arise in using Twitter data. We discuss various keyword methods, as well as methods for classifying a user as \"sick\". We discuss some of our successes and failures and provide some insight into the utility and limitations of Twitter. We discuss variations on the basic surveillance theme such as watching for a known disease, a known set of symptoms, and the more general problem of detecting an unusual number of sick individuals within a county.