scholarly journals Big Data Opportunities for Global Infectious Disease Surveillance

PLoS Medicine ◽  
2013 ◽  
Vol 10 (4) ◽  
pp. e1001413 ◽  
Author(s):  
Simon I. Hay ◽  
Dylan B. George ◽  
Catherine L. Moyes ◽  
John S. Brownstein
2016 ◽  
Vol 214 (suppl 4) ◽  
pp. S409-S413 ◽  
Author(s):  
Elizabeth C. Lee ◽  
Jason M. Asher ◽  
Sandra Goldlust ◽  
John D. Kraemer ◽  
Andrew B. Lawson ◽  
...  

2019 ◽  
Vol 10 (1) ◽  
pp. 94-115
Author(s):  
Stephen L ROBERTS

This article investigates the rise of algorithmic disease surveillance systems as novel technologies of risk analysis utilised to regulate pandemic outbreaks in an era of big data. Critically, the article demonstrates how intensified efforts towards harnessing big data and the application of algorithmic processing techniques to enhance the real-time surveillance and regulation infectious disease outbreaks significantly transform practices of global infectious disease surveillance; observed through the advent of novel risk rationalities which underpin the deployment of intensifying algorithmic practices to increasingly colonise and patrol emergent topographies of data in order to identify and govern the emergence of exceptional pathogenic risks. Conceptually, this article asserts further howthe rise of these novel risk regulating technologies within a context of big data transforms the government and forecasting of epidemics and pandemics: illustrated by the rise of emergent algorithmic governmentalties of risk within contemporary contexts of big data, disease surveillance and the regulation of pandemic.


2016 ◽  
Vol 214 (suppl 4) ◽  
pp. S380-S385 ◽  
Author(s):  
Lone Simonsen ◽  
Julia R. Gog ◽  
Don Olson ◽  
Cécile Viboud

2016 ◽  
Vol 214 (suppl 4) ◽  
pp. S375-S379 ◽  
Author(s):  
Shweta Bansal ◽  
Gerardo Chowell ◽  
Lone Simonsen ◽  
Alessandro Vespignani ◽  
Cécile Viboud

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