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Forecasting rare disease outbreaks from open source indicators

Rapidly increasing volumes of news feeds from diverse data sources, such as online newspapers, Twitter, and online blogs, are proving to be extremely valuable resources in helping to anticipate, detect, and forecast outbreaks of rare diseases. The goal of this paper is to develop techniques that can effectively forecast the emergence and progression of rare infectious diseases by combining data from disparate data sources.