Disease spread is major health concern around the world and it is compounded by the increasing globalization of our society. As such, epidemiological modeling approaches need to account for rapid changes in human behavior and community perceptions. Social media has recently played a crucial role in informing and changing people's response to the spread of infectious diseases. I will describe a modeling framework that simulates the movements, activities, and social interactions of millions of individuals, and the dynamics of infectious diseases. The simulation allows for agents' behaviors to be influenced by social media (i.e., Twitter) as well as by their neighbors. This feedback loop allows us to inject emergent attitudes in response to epidemics and quantify their impact. In addition, I will describe how Internet data streams are informing models to better forecast disease spread.