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An Infectious Disease Outbreak Simulator Based on the Cellular Automata Paradigm

  • Sangeeta Venkatachalam
  • Armin R. Mikler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3473)

Abstract

In this paper, we propose the use of Cellular Automata paradigm to simulate an infectious disease outbreak. The simulator facilitates the study of dynamics of epidemics of different infectious diseases, and has been applied to study the effects of spread vaccination and ring vaccination strategies. Fundamentally the simulator loosely simulates SIR (Susceptible Infected Removed) and SEIR (Susceptible Exposed Infected Removed). The Geo-spatial model with global interaction and our approach of global stochastic cellular automata are also discussed. The global stochastic cellular automata takes into account the demography, culture of a region. The simulator can be used to study the dynamics of disease epidemics over large geographic regions. We analyze the effects of distances and interaction on the spread of various diseases.

Keywords

Cellular Automaton Contact Rate Infectious Period Global Interaction Infectious Disease Outbreak 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Ahmed, E., Agiza, H.N.: On Modeling epidemics. Including latency, incubation and variable susceptibility Physica A 253, 347–352 (1998)Google Scholar
  2. 2.
    Ahmed, E., Elgazzar, A.S.: On some applications of cellular automata. Physica A 296, 529–538 (2002)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Bagni, R., Berchi, R., Cariello, P.: A comparison of simulation models applied to epidemics. Journal of Artificial Societies and Social Simulation 5, 3 (2002)Google Scholar
  4. 4.
    Barfoot, T.D., D’Eleuterio, G.M.T.: Multiagent Coordination by Stochastic Cellular Automata. Presented at the International Joint Conference on Artificial Intelligence (2001)Google Scholar
  5. 5.
    Boccara, N., Cheong, K.: Critical behavior of a probabilistic automata network SIS model for the spread of an infectious disease in a population of moving individuals. Journal of Physics A:Mathematical and General 26(5), 3707–3717 (1993)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Boccara, N., Cheong, K., Oram, M.: A probabilistic automata network epidemic model with births and deaths exhibiting cyclic behavior. Journal of Physics A:Mathematical and General 27, 1585–1597 (1994)zbMATHCrossRefGoogle Scholar
  7. 7.
    Del Giudice, G.: Vaccine. 21 Suppl 2:S83-8 (2003)Google Scholar
  8. 8.
    Stefano, B.D., Fukś, H., Lawniczak, A.T.: Object-oriented implementation of CA/LGCA modelling applied to the spread of epidemics. In: 2000 Canadian Conference on electrical and Computer Engineering, vol. 1, pp. 26–31. IEEE, Los Alamitos (2000)Google Scholar
  9. 9.
    Fukś, H., Lawniczak, A.T.: Individual-based lattice model for spatial spread of epidemics. Discrete Dynamics in Nature and Society 6, 191–200 (2001)zbMATHCrossRefGoogle Scholar
  10. 10.
    Situngkir, H.: Epidemiology through Cellular Automata Case of Study: Avian Influenza Indonesia Working Paper WPF, Bandung Fe Institute (2004)Google Scholar
  11. 11.
    Thomas, J.C., Weber, D.J.: Epidemiologic Methods for the Study of Infectious Diseases. Oxford Press, Oxford (2001)Google Scholar
  12. 12.
    Kleczkowski, A., Grenfell, B.T.: Mean-field-type equations for spread of epidemics: The ‘small world’ model. Physica A 274(1-2), 355–360 (1999)CrossRefGoogle Scholar
  13. 13.
    Mansilla, R., Gutierrez, J.L.: Deterministic site exchange cellular automata models for the spread of diseases in human settlements. Bulletin of Mathematical BiologyGoogle Scholar
  14. 14.
    Fu, S.C., Milne, G.: Epidemic Modelling Using Cellular Automata. To appear in Australian Conference on Artificial Life (2003)Google Scholar
  15. 15.
    Wolfram, S.: Statistical Mechanics of Cellular Automata. Reviews of Modern. Physics 55, 601–644Google Scholar
  16. 16.
    Yaganehdoost, A., Graviss, E.A., Ross, M.W., et al.: Complex transmission dynamics of clonally related virulent Mycobacterium tuberculosis associated with barhopping by predominantly human immunodeficiency virus-positive gay men. Journal of Infect Diseases 180(4), 1245–1251 (1999)CrossRefGoogle Scholar
  17. 17.
    Youngblut, C.: Educational uses of virtual reality technology. Technical Report IDA Document D-2128, Institute for Defense Analyses, Alexandria, VA (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sangeeta Venkatachalam
    • 1
  • Armin R. Mikler
    • 1
  1. 1.Department of Computer ScienceUniversity of North TexasDentonUSA

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