Spatial epidemiology project

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Epidemic simulation
Stochastic S-I-R simulation of the spread of an epidemic in South America, from an initial focus in Manaus, Brazil. The map projection is Azimuthal Equal-Area.

Contents

Description

Research in this project is focused on the following topics (in no particular order):

  • What is the best discrete-time discrete-space form of the reaction-diffusion equations for modeling real-world epidemics?
  • In the Hoppenstaedt version of the spatial epidemic, should the kernel function be scale-free?
  • How can we best incorporate mass movements of populations as they flee a major epidemic?
  • Which versions of the Ensemble Kalman Filter (EnKF) work the best for tracking epidemics?
  • Might a particle filter operated by a genetic algorithm perform better than an ensemble filter?
  • In any filter used for tracking purposes, should we apply the filter to a transformed state space?
  • How can we best model transportation networks?
  • How can we best estimate the epidemic's parameters?

Overall leadership of this project lies with Dr. Loren Cobb, of the Department of Mathematical and Statistical Sciences.

Funding

  • The spatial epidemiology project of the Center for Computational Mathematics was funded by a two-year Challenge Grant from the National Library of Medicine from October 2009 to September 2011.

Publications

Journal papers

Conference proceedings and book chapters

  • Jan Mandel, Jonathan D. Beezley, Loren Cobb, and Ashok Krishnamurthy, "Data Driven Computing by the Morphing Fast Fourier Transform Ensemble Kalman Filter in Epidemic Spread Simulations", Procedia Computer Science, vol 1, 1215–23, May 2010. arXiv:1003.1771 CCM Report 285 paper UCD
  • Ashok Krishnamurthy, Loren Cobb, Jan Mandel, and Jonathan D. Beezley, Bayesian Tracking of Emerging Epidemics Using Optimal Statistical Interpolation, 2010 Joint Statistical Meetings, Vancouver, Canada, July 31- August 5, 2010, pp. 3471-3485. arXiv:1009.4959pdf abstract
  • Jonathan D. Beezley, Jan Mandel, and Loren Cobb, Wavelet Ensemble Kalman Filters, Proceedings of the 6th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS'2011), Prague, September 15--17, 2011, 514--518, 2011, ISBN 978-1-4577-1423-8. arXiv:1102.5554

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