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Computational epidemiology is a multidisciplinary field that uses techniques from computer science, mathematics, geographic information science and public health to better understand issues central to epidemiology such as the spread of diseases or the effectiveness of a public health intervention.
In contrast with traditional epidemiology, computational epidemiology looks for patterns in unstructured sources of data, such as social media. It can be thought of as the hypothesis-generating antecedent to hypothesis-testing methods such as national surveys and randomized controlled trials.
- Harvard Medical School Children's Hospital Boston Computational Epidemiology Group
- University of Iowa Computational Epidemiology Group (Compepi)
- The Center for Computational Epidemiology, Bioinformatics and Risk Analysis (CCEBRA) at Tuskegee University
- The Institute for Disease Modeling
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