Social Network Disease Analysis
Manan A. Shah 1 and Rok Sosic 2
1Student at the Harker School, San Jose, CA, USA
2The InfoLab, Stanford University School of Engineering, Stanford, CA, USA
Figure 1: An illustration of disease spread across a real airport network as a function of time.
Disease spread, both locally and across continents, has been studied in various medical contexts; however, the problem has yet to be thoroughly analyzed from an informatics standpoint. In this work, we plan to incorporate the vast array of big data presently available--specifically tweets on the social media site Twitter--in an attempt to model and predict disease genesis and dispersion over time. We further work towards generating cohesive equation-based models in the hope of comparing the results obtained from social media with both CDC ILI distributions and simulation curves.