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Abstract Details
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Activity Number:
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479
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #303319 |
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Title:
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Tracking Emerging Infectious Disease Epidemics in Real Time Using Spectral Bayesian Data Assimilation
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Author(s):
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Ashok Krishnamurthy*+ and Jonathan Beezley and Loren Cobb and Jan Mandel
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Companies:
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University of Colorado at Denver and University of Colorado at Denver and University of Colorado at Denver and University of Colorado at Denver
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Address:
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1175 Albion St Apt 409, Denver, CO, 80220, United States
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Keywords:
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spatial epidemiology ;
data assimilation ;
disease tracking ;
bayesian design ;
traveling wave ;
FFT
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Abstract:
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We apply a discretized stochastic version of the spatial susceptible-infectious-removed (S-I-R) compartmental model of epidemiology to track in real time the incidence on new cases of a fast moving simulated traveling wave of an infectious disease epidemic. We use spectral approximation of the covariance by FFT and wavelets to obtain fast methods that can handle spatial simulations with large state vectors on a laptop in real time. These improved tracking methods derive their speed gains from smaller required ensemble sizes and more efficient algebra. Finally, we extend our methods to incorporate long-distance transportation, in order to track the rapid geographical spread of infectious diseases in human populations.
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