Advertisement

Grid Computing for Disaster Mitigation

  • Hock Lye Koh
  • Su Yean Teh
  • Taksiah A. Majid
  • Hamidi Abdul Aziz
Conference paper

Abstract

The infamous 2004 Andaman tsunami has highlighted the need to be prepared and to be resilient to such disasters. Further, recent episodes of infectious disease epidemics worldwide underline the urgency to control and manage infectious diseases. Universiti Sains Malaysia (USM) has recently formed the Disaster Research Nexus (DRN) within the School of Civil Engineering to spearhead research and development in natural disaster mitigation programs to mitigate the adverse effects of natural disasters. This paper presents a brief exposition on the aspirations of DRN towards achieving resilience in communities affected by these natural disasters. A brief review of the simulations of the 2004 Andaman tsunami, with grid application is presented. Finally, the application of grid technology in large scale simulations of disease transmission dynamics is discussed.

Keywords

Tsunami disease grid simulation high performance computing 

References

  1. 1.
    Derouich, M. & Boutayeb, A. (2006). Dengue fever: Mathematical modeling and computer simulation. Applied Mathematics and Computation 177, 528-544.zbMATHCrossRefMathSciNetGoogle Scholar
  2. 2.
    Esteva, L. & Vargas, C. (1998). Analysis of a dengue disease transmission model. Mathematical Biosciences 150, 131-151.zbMATHCrossRefGoogle Scholar
  3. 3.
    Focks, D. A., Haile, D. C., Daniels, E. & Moun, G. A. (1993). Dynamics life table model for Aedes Aegypti: Analysis of the literature and model development. Journal of Medical Entomology 30, 1003-1018.Google Scholar
  4. 4.
    Gratz, N. G. (1991). Emergency control of Aedes aegypti as a disease vector in urban areas. Journal of the American Mosquito Control Association 7, 353-365.Google Scholar
  5. 5.
    Hopp, M. J. & Foley, J. A. (2003). Worldwide fluctuations in dengue fever cases related to climate variability. Climate Research 25, 85-94.CrossRefGoogle Scholar
  6. 6.
    Koh, H.L., Teh, S.Y., Izani, A.M.I. & DeAngelis, D.L. (2008). Modeling Biological Invasion: The Case of Dengue and Mangrove. Invited Lecture in International Conference on Mathematical Biology – ICMB07. American Institute of Physics Conference Proceedings, Volume 971, New York, p. 11-18.Google Scholar
  7. 7.
    Koh, H.L., Teh, S.Y., Liu, P.L.-F., Izani, A.M.I. & Lee, H.L. (2009a). Simulation of Andaman 2004 Tsunami for Assessing Impact on Malaysia. Journal of Asian Earth Sciences 36, 74-83.CrossRefGoogle Scholar
  8. 8.
    Koh, H.L., Teh, S.Y., Izani, A.M.I., Lee, H.L. & Kew, L.M. (2009b). Simulation of Future Andaman Tsunami into Straits of Malacca by TUNA. Journal of Earthquakes and Tsunamis 3 (2), 89-100.CrossRefGoogle Scholar
  9. 9.
    Patz, J. A., Martens, W.J.M., Focks, D. A. & Jetten, T. H. (1998). Dengue Fever Epidemic Potential as Projected by General Circulation Models of Global Climate Change. Environmental Health Perspective 106(3), 147-153.Google Scholar
  10. 10.
    Reiter, P. (2001). Climate Change and Mosquito-Borne Disease. Environmental Health Perspectives 109, 141-161.CrossRefGoogle Scholar
  11. 11.
    Rueda, L. M. Patel, K. J., Axtell, R. C. & Stinner, R. E. (1990). Temperature-dependent development and survival rates of culex quinquefasciatus and aedes aegypti (diptera: Culicidae). Journal of Medical Entomology 27, 892-898.Google Scholar
  12. 12.
    Schoofield, R. M., Sharpe, P. J. H. & Magnuson, C. E. (1981). Non-linear regression of biological temperature-dependent rate models based on an absolute reaction-rate theory. Journal of Theoretical Biology 88, 719-731.CrossRefGoogle Scholar
  13. 13.
    Shaman, J., Spiegelman, M., Cane, M. & Stieglitz, M. (2005). A hydrologically driven model of swamp water mosquito population dynamics. Ecological Modelling 194, 395-404.CrossRefGoogle Scholar
  14. 14.
    Tan, K.B., Koh, H.L. & Teh, S.Y. (2009). Modeling Dengue Fever Subject to Temperature Change. Proceedings of the 6th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'09), Volume 5, 14-16 August 2009, Tianjin, China. The Institute of Electrical and Electronics Engineers (IEEE), USA, p. 61-65.Google Scholar
  15. 15.
    Teh, S.Y., Koh, H.L., Liu, P.L.-F., Izani, A.M.I. & Lee, H.L. (2009). Analytical and Numerical Simulation of Tsunami Mitigation by Mangroves in Penang, Malaysia. Journal of Asian Earth Sciences 36, 38-46.CrossRefGoogle Scholar
  16. 16.
    Yang, H. M. & Ferreira, C. P. (2007). Assessing the effects of vector control on dengue transmission. Applied Mathematics and Computation 198, 401-413CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Hock Lye Koh
    • 1
  • Su Yean Teh
    • 2
  • Taksiah A. Majid
    • 1
  • Hamidi Abdul Aziz
    • 1
  1. 1.Disaster Research Nexus, School of Civil Engineering, Engineering CampusUniversiti Sains MalaysiaKubang KerianMalaysia
  2. 2.School of Mathematical SciencesUniversiti Sains MalaysiaKubang KerianMalaysia

Personalised recommendations