Big Data and Analytics for Infectious Disease Research, Operations, and Policy Proceedings of a Workshop (2016) / Chapter Skim
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1 Introduction
1 Introduction
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Advances in machine learning and crowdsourcing may also offer the possibility to gather information about disease dynamics, such as contact patterns and the impact of the social environment. New, rapid, point-of-care diagnostics may make it possible to capture not only diagnostic information but also other potentially epidemiologically relevant information in real time.
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The Forum on Microbial Threats convened a 1.5-day workshop in Washington, DC, to explore some of the opportunities and issues associated with the scientific, policy, and operational aspects of big data in relation to microbial threats and public health.2 The workshop was organized by an ad hoc committee whose members were Scott Dowell, Jennifer Gardy, Margaret Hamburg, Kent Kester, Lonnie King (Chair) , George Poste, Martin Sepúlveda, Jay Siegel, and Lance Waller.
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