The analysis of real time search queries-the so-called ''searchstream''-has been shown to be a sensitive and timely means of evaluating geographically-specific trends in influenza; both Yahoo and Google search engines have proven to be powerful tools for influenza surveillance [22, 23] . More recently, evaluation of data from the microblogging website Twitter has been shown to provide useful information about both disease activity and disease concern related to the 2009 influenza pandemic [15] . Finally, the widespread availability of smartphone technologies makes it possible to interact with population members to elicit information on illness (so-called ''crowdsourcing''), and also (by using cellphone or smartphone network data) to evaluate the movement of populations, which may be a key predictor of how epidemics spread [24] [25] [26] . This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication. Readers unfamiliar with these approaches may wish to try a simple experiment using the Google Insights for Search tool, which provides a graphical depiction of both search term volumes and online media reports of disease (http://www.google.com/ insights/search/#). Searches on terms such as ''norovirus'' or ''pneumonia'' produce seasonally oscillating patterns of searches as one might anticipate in diseases with strong wintertime seasonality (Figure 1) , and which is presumably generated by individuals who have, or know someone who has, this diagnosis seeking to learn more about it online. However, the pitfalls of this approach can be appreciated in a similar manner: a search on the term ''influenza'' produces a graph with a tremendous spike in 2009 ( Figure 2) ; indeed a spike so large that it obscures influenza activity in all other years. This reflects the difficulties that searchstream-based surveillance methods may encounter when evaluating diseases that generate extreme public concern or media attention.