There is an interesting article in the MIT technology review about a research project called “Reality Mining” that was tangentially related to our discussion of disease today in lecture. In partnership with Nokia Research, Nathan Eagle, a doctoral student, and his advisor, Sandy Pentland use mobile phones to collect data about user behavior. This data collection is based on call logs and bluetooth radios which report the user’s proximity to other bluetooth enabled devices (roughly 10m range). In the future, data from GPS chips and accelerometers might be incorporated as well to build more sophisticated models of behavior. 
The researchers suggest that they are able to identify significant locations and to build an understanding of inter-personal relationships between users.  This process of interpreting the data collected by the mobile phones is termed “reality mining”. As defined by Pentland, this reality mining, “is all about paying attention to patterns in life and using that information to help [with] things like setting privacy patterns, sharing things with people, notifying people–basically, to help you live your life.” 
The future directions of this work (beyond automatically setting preferences based on context and managing privacy) are particularly interesting. Eagle plans to use this mobile phone based reality mining to understand how diseases are spread, and to improve the current computational models. Eagle adds, “what’s interesting is that you can see that a disease spreads based on who is infected first.” Imagine if instead of relying on the self-reports of each hospitalized victim, public health officials could instead analyze mobile data using reality mining techniques to determine the path and more effectively enforce quarantine. 
http://www.technologyreview.com/read_article.aspx?ch=specialsections&sc=emerging08&id=20247http://reality.media.mit.edu/publications.php