Imagine two broad scenarios where a rapid point-of-care diagnostic would be useful to detect dangerous viruses. The first scenario is one where patients appear at a clinic, possibly in a rural area lacking sophisticated medical technologies, with fever of unknown origin. Identifying the source of the fever is critical for immediate patient care, for avoiding disease spread, and for preventing the current disease from progressing to a more dangerous form. The second scenario is a bioterror attack, where a pathogen is weaponized and delivered to a populated area. Here, rapid identification of the pathogen is essential for appropriate medical care and for preventing further spread.
The Gehrke lab collaborates with engineers from the MIT D-Lab, from the Biological Engineering Department, and from the Department of Electrical Engineering and Computer Science to design and develop rapid point-of-care diagnostics to detect dangerous viruses. The approach is based primarily on lateral flow chromatography and mobile phone communications to record and analyze data. We think about this problem in terms of a “citizen sensor” where diagnosis and real-time epidemiology can take place not only in hospitals and clinics, but also in the field at the site of infections. We are also intrigued by current developments in social network data analysis, and the possible impact of these data on early detection of disease epidemics (for example see this paper by Fowler and Christakis).