Current surveillance estimates for reportable respiratory infections are based on disease reports through provider- and laboratory-based reporting mechanisms. We have proposed a methodology to correlate disease prevalence based on symptom reports from search data with routine surveillance reports and hospital discharge data, in order to develop new prediction tools for public health surveillance (e.g. RSV). We are currently exploring social patterning of diseases through the use of social media-based reports over time, as well as the role of misinformation. Our current work examines both Hepatitis A and Influenza.