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|a 9780309450119
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|a 030945011X
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|a Alper, Joe
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|a Big data and analytics for infectious disease research, operations, and policy
|h Elektronische Ressource
|b proceedings of a workshop
|c Forum on Microbial Threats, Board on Global Health, Health and Medicine Division, the National Academies of Sciences, Engineering, Medicine
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|a Washington, DC
|b National Academies Press
|c [2016], 2016
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|a 1 PDF file (xvi, 81 pages)
|b illustrations
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|a Includes bibliographical references
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|a Communicable Diseases / epidemiology
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|a Global Health
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|a Population Surveillance
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|a Datasets as Topic
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|a National Academies of Sciences, Engineering, and Medicine (U.S.)
|b Forum on Microbial Threats
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|a Workshop on Big Data and Analytics for Infectious Disease Research, Operations, and Policy (2016, Washington, D.C.)
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|a eng
|2 ISO 639-2
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|b NCBI
|a National Center for Biotechnology Information
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|u https://www.ncbi.nlm.nih.gov/books/NBK401690
|3 Volltext
|n NLM Bookshelf Books
|3 Volltext
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|a 380
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|a 610
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|a With the amount of data in the world exploding, big data could generate significant value in the field of infectious disease. The increased use of social media provides an opportunity to improve public health surveillance systems and to develop predictive models. 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. With a wide range of data available for analysis, decision-making and policy-making processes could be improved. While there are many opportunities for big data to be used for infectious disease research, operations, and policy, many challenges remain before it is possible to capture the full potential of big data. In order 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, the National Academies of Sciences, Engineering, and Medicine convened a workshop in May 2016. Participants discussed a range of topics including preventing, detecting, and responding to infectious disease threats using big data and related analytics; varieties of data (including demographic, geospatial, behavioral, syndromic, and laboratory) and their broader applications; means to improve their collection, processing, utility, and validation; and approaches that can be learned from other sectors to inform big data strategies for infectious disease research, operations, and policy. This publication summarizes the presentations and discussions from the workshop
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