Computational epidemiology

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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.

Recently, the University of North Texas founded the Center for Computational Epidemiology and Response Analysis (CeCERA) as a collaboration of faculties from the fields of computer science, public health, medical geography, and geographic information science.[citation needed]

Introduction[edit]

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.


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