Difference between revisions of "2014 ISISANetworkedEpidemiologybased"

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* ([[2014_ISISANetworkedEpidemiologybased|Beckman et al., 2014]]) ⇒ [[author::Richard Beckman]], [[author::Keith R. Bisset]], [[author::Jiangzhuo Chen]], [[author::Bryan Lewis]], [[author::Madhav Marathe]], and [[author::Paula Stretz]]. ([[year::2014]]). “ISIS: A Networked-epidemiology based Pervasive Web App for Infectious Disease Pandemic Planning and Response.” In: [[proceedings::Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]] ([[conference::KDD-2014]]) Journal. ISBN:978-1-4503-2956-9 [http://dx.doi.org/10.1145/2623330.2623375 doi:10.1145/2623330.2623375]  
 
* ([[2014_ISISANetworkedEpidemiologybased|Beckman et al., 2014]]) ⇒ [[author::Richard Beckman]], [[author::Keith R. Bisset]], [[author::Jiangzhuo Chen]], [[author::Bryan Lewis]], [[author::Madhav Marathe]], and [[author::Paula Stretz]]. ([[year::2014]]). “ISIS: A Networked-epidemiology based Pervasive Web App for Infectious Disease Pandemic Planning and Response.” In: [[proceedings::Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining]] ([[conference::KDD-2014]]) Journal. ISBN:978-1-4503-2956-9 [http://dx.doi.org/10.1145/2623330.2623375 doi:10.1145/2623330.2623375]  
  
<B>Subject Headings:</B>  
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<B>Subject Headings:</B> [[Computational Epidemiology]].
  
 
==Notes==
 
==Notes==
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This identified the guiding principle that</i>[[complex model]]s will be used by [[domain expert]]s only if they can do [[realistic analysis]] without becoming [[computing expert]]s</i>. </s>
 
This identified the guiding principle that</i>[[complex model]]s will be used by [[domain expert]]s only if they can do [[realistic analysis]] without becoming [[computing expert]]s</i>. </s>
  
Using [[ISIS]], one can carry out detailed [[computational experiment]]s as they pertain to [[planning and response in the event]] of a [[pandemic]]. </s>
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Using [[ISIS]], one can carry out detailed [[computational experiment]]s as they pertain to [[planning]] and [[response]] in the [[event of a pandemic]]. </s>
 
[[ISIS]] is designed to [[support networked epidemiology]] -- [[study]] of [[epidemic process]]es over [[social contact network]]s. </s>
 
[[ISIS]] is designed to [[support networked epidemiology]] -- [[study]] of [[epidemic process]]es over [[social contact network]]s. </s>
 
The [[current system]] can handle [[airborne infectious disease]]s such as [[influenza]], [[pertussis]], and [[smallpox]]. </s>
 
The [[current system]] can handle [[airborne infectious disease]]s such as [[influenza]], [[pertussis]], and [[smallpox]]. </s>

Revision as of 16:48, 26 March 2020

Subject Headings: Computational Epidemiology.

Notes

Cited By

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Author Keywords

Abstract

We describe ISIS, a high-performance-computing-based application to support computational epidemiology of infectious diseases. ISIS has been developed over the last seven years in close coordination with public health and policy experts. It has been used in a number of important federal planning and response exercises. ISIS grew out of years of experience in developing and using HPC-oriented models of complex socially coupled systems. This identified the guiding principle thatcomplex models will be used by domain experts only if they can do realistic analysis without becoming computing experts.

Using ISIS, one can carry out detailed computational experiments as they pertain to planning and response in the event of a pandemic. ISIS is designed to support networked epidemiology -- study of epidemic processes over social contact networks. The current system can handle airborne infectious diseases such as influenza, pertussis, and smallpox. ISIS is comprised of the following basic components: (i) a web app that serves as the user-interface, (ii) a middleware that coordinates user interaction via the web app with backend models and databases, (iii) a backend computational modeling framework that is comprised of highly resolved epidemic simulations combined with highly realistic control strategies that include pharmaceutical as well as non-pharmaceutical interventions and (iv) a backend data management framework that manages complex unstructured and semi-structured data.

ISIS has been used in over a dozen case studies defined by the DoD, DHHS, NIH, BARDA and NSC. We describe three recent studies illustrating the use of ISIS in real-world settings: (i) uses of ISIS during the H1N1 pandemic, ii) supporting a US military planning exercise, and (iii) distribution of limited stockpile of pharmaceuticals using public and private outlets.

References

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2014 ISISANetworkedEpidemiologybasedRichard Beckman
Keith R. Bisset
Jiangzhuo Chen
Bryan Lewis
Madhav Marathe
Paula Stretz
ISIS: A Networked-epidemiology based Pervasive Web App for Infectious Disease Pandemic Planning and Response10.1145/2623330.26233752014