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Difference between revisions of "Next Generation Surveillance for the Next Pandemic"

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'''Organizers'''
 
'''Organizers'''
The workshop was organized by Sam Scarpino and Ben Althouse, both Omidyar Fellows at the Santa Fe Institute.
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The workshop was organized by [http://santafe.edu/about/people/profile/Sam%20Scarpino Sam Scarpino] and [http://santafe.edu/about/people/profile/Ben%20Althouse Ben Althouse] both Omidyar Fellows at the Santa Fe Institute.
  
 
'''Meeting Abstract'''
 
'''Meeting Abstract'''
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Effectively responding to the next pandemic will require robust, timely, and informative surveillance. While traditional surveillance has been invaluable in recognizing and controlling novel pandemics, it is often delayed and limited in geographic resolution. A promising addition to the ecosystem of surveillance systems are new technology-enabled sources such as Google Flu Trends, Biosense 2.0, FluNearYou, and Mappy Health. These next generation surveillance techniques provide a potential wealth of temporal and geographic information beyond that of existing systems.  This high-resolution information can also be used to advance and validate existing dynamical models for disease transmission and control.  However, it is unclear which data streams are most appropriate and how to best integrate them: some are expensive, others provide noisy data, others yet are unreliable. The proposed workshop has three primary goals: (1) to facilitate an exchange of ideas on next generation surveillance between researchers, entrepreneurs, and public health decision makers (2) advance our theoretical understanding of the ecological and evolutionary dynamics of infectious diseases, and (3) produce a set of actionable results for integrating these new data into surveillance for the next pandemic.
 
Effectively responding to the next pandemic will require robust, timely, and informative surveillance. While traditional surveillance has been invaluable in recognizing and controlling novel pandemics, it is often delayed and limited in geographic resolution. A promising addition to the ecosystem of surveillance systems are new technology-enabled sources such as Google Flu Trends, Biosense 2.0, FluNearYou, and Mappy Health. These next generation surveillance techniques provide a potential wealth of temporal and geographic information beyond that of existing systems.  This high-resolution information can also be used to advance and validate existing dynamical models for disease transmission and control.  However, it is unclear which data streams are most appropriate and how to best integrate them: some are expensive, others provide noisy data, others yet are unreliable. The proposed workshop has three primary goals: (1) to facilitate an exchange of ideas on next generation surveillance between researchers, entrepreneurs, and public health decision makers (2) advance our theoretical understanding of the ecological and evolutionary dynamics of infectious diseases, and (3) produce a set of actionable results for integrating these new data into surveillance for the next pandemic.

Latest revision as of 15:59, 21 April 2014

Workshop Navigation

Organizers

The workshop was organized by Sam Scarpino and Ben Althouse both Omidyar Fellows at the Santa Fe Institute.

Meeting Abstract

Effectively responding to the next pandemic will require robust, timely, and informative surveillance. While traditional surveillance has been invaluable in recognizing and controlling novel pandemics, it is often delayed and limited in geographic resolution. A promising addition to the ecosystem of surveillance systems are new technology-enabled sources such as Google Flu Trends, Biosense 2.0, FluNearYou, and Mappy Health. These next generation surveillance techniques provide a potential wealth of temporal and geographic information beyond that of existing systems. This high-resolution information can also be used to advance and validate existing dynamical models for disease transmission and control. However, it is unclear which data streams are most appropriate and how to best integrate them: some are expensive, others provide noisy data, others yet are unreliable. The proposed workshop has three primary goals: (1) to facilitate an exchange of ideas on next generation surveillance between researchers, entrepreneurs, and public health decision makers (2) advance our theoretical understanding of the ecological and evolutionary dynamics of infectious diseases, and (3) produce a set of actionable results for integrating these new data into surveillance for the next pandemic.