Infodemiology metrics have a number of potential applications. For example, in the context of public health and syndromic surveillance, we were - in an early proof-of-concept project - the first to observe a correlation between Google searches and influenza incidence (Eysenbach, 2006), suggesting demand-based infodemiology metrics as a candidate for early detection of disease outbreaks - this idea was later popularized and commercially exploited by Google (Google Flutrends). There are also various applications related to knowledge translation - for exmple, we are experimenting with tools enabling us to measure the "penetration" rate and patterns with which new knowledge or new information is disseminated.
We are currently focussing on Twitter as data source, and H1N1 as "concept of interest" (COI). We have developed generic tools that enable us to 1) gather and archive COI-relevant tweets as well as COI-relevant webpages, blogs, and other web-based material, 2) generate geospatial metircs (indices), 3) visualize and analyze these data, e.g. on maps. We are also working on the idea to combine passive data collection methods with active collection methods (online surveys).