I'm back again -- three posts back to back about public health related to viruses! A vital part of public health is to be able to predict the course of the progression of disease. Based on research from MIT, there is a new model to predict the progression of disease and social networks contributing to responses to outbreaks. They have devised a method to analyze social media messages, hospital records, and other information sources about the incidence and progression of disease. Their study is based upon studying 3 different outbreaks -- the 2009 H1N1 outbreaks in Mexico and Hong Kong along with the 2003 SARS outbreak in Hong Kong. They determined that the public health responses were often disproportionate to the actual risk posed in these outbreaks. Additionally, they identified various events that can interfere with the public health measures that are implemented and can worsen the disease spread. An interesting point is that the disease spread may be increased because of publicity, leading to public health facilities being over-populated. This research and the resulting computational technology may be able to help best allocate resources to facilitate public health resources to large-scale epidemics in the future.