IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i3p540-548.html
   My bibliography  Save this article

Parameter inference in small world network disease models with approximate Bayesian Computational methods

Author

Listed:
  • Walker, David M.
  • Allingham, David
  • Lee, Heung Wing Joseph
  • Small, Michael

Abstract

Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome.

Suggested Citation

  • Walker, David M. & Allingham, David & Lee, Heung Wing Joseph & Small, Michael, 2010. "Parameter inference in small world network disease models with approximate Bayesian Computational methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(3), pages 540-548.
  • Handle: RePEc:eee:phsmap:v:389:y:2010:i:3:p:540-548 DOI: 10.1016/j.physa.2009.09.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437109008309
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hughes, Roger L., 2002. "A continuum theory for the flow of pedestrians," Transportation Research Part B: Methodological, Elsevier, vol. 36(6), pages 507-535, July.
    2. Henein, Colin M. & White, Tony, 2007. "Macroscopic effects of microscopic forces between agents in crowd models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 373(C), pages 694-712.
    3. Weifeng, Fang & Lizhong, Yang & Weicheng, Fan, 2003. "Simulation of bi-direction pedestrian movement using a cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 321(3), pages 633-640.
    4. Blue, Victor J. & Adler, Jeffrey L., 2001. "Cellular automata microsimulation for modeling bi-directional pedestrian walkways," Transportation Research Part B: Methodological, Elsevier, vol. 35(3), pages 293-312, March.
    5. Kirchner, Ansgar & Klüpfel, Hubert & Nishinari, Katsuhiro & Schadschneider, Andreas & Schreckenberg, Michael, 2003. "Simulation of competitive egress behavior: comparison with aircraft evacuation data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(3), pages 689-697.
    6. Dirk Helbing & Lubos Buzna & Anders Johansson & Torsten Werner, 2005. "Self-Organized Pedestrian Crowd Dynamics: Experiments, Simulations, and Design Solutions," Transportation Science, INFORMS, vol. 39(1), pages 1-24, February.
    7. Tajima, Yusuke & Takimoto, Kouhei & Nagatani, Takashi, 2002. "Pattern formation and jamming transition in pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 313(3), pages 709-723.
    8. Muramatsu, Masakuni & Nagatani, Takashi, 2000. "Jamming transition in two-dimensional pedestrian traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 275(1), pages 281-291.
    9. Burstedde, C & Klauck, K & Schadschneider, A & Zittartz, J, 2001. "Simulation of pedestrian dynamics using a two-dimensional cellular automaton," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 295(3), pages 507-525.
    10. Song, Weiguo & Xu, Xuan & Wang, Bing-Hong & Ni, Shunjiang, 2006. "Simulation of evacuation processes using a multi-grid model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 492-500.
    11. Muramatsu, Masakuni & Nagatani, Takashi, 2000. "Jamming transition of pedestrian traffic at a crossing with open boundaries," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 286(1), pages 377-390.
    12. Isobe, Motoshige & Adachi, Taku & Nagatani, Takashi, 2004. "Experiment and simulation of pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 336(3), pages 638-650.
    13. Yamamoto, Kazuhiro & Kokubo, Satoshi & Nishinari, Katsuhiro, 2007. "Simulation for pedestrian dynamics by real-coded cellular automata (RCA)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 654-660.
    14. Jian, Li & Lizhong, Yang & Daoliang, Zhao, 2005. "Simulation of bi-direction pedestrian movement in corridor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 354(C), pages 619-628.
    15. Kirchner, Ansgar & Schadschneider, Andreas, 2002. "Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 312(1), pages 260-276.
    16. Daoliang, Zhao & Lizhong, Yang & Jian, Li, 2006. "Exit dynamics of occupant evacuation in an emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 501-511.
    17. Mitchell, David H. & MacGregor Smith, J., 2001. "Topological network design of pedestrian networks," Transportation Research Part B: Methodological, Elsevier, vol. 35(2), pages 107-135, February.
    18. Takimoto, Kouhei & Tajima, Yusuke & Nagatani, Takashi, 2002. "Effect of partition line on jamming transition in pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 308(1), pages 460-470.
    19. Weng, W.G. & Shen, S.F. & Yuan, H.Y. & Fan, W.C., 2007. "A behavior-based model for pedestrian counter flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 668-678.
    20. Yue, Hao & Hao, Herui & Chen, Xiaoming & Shao, Chunfu, 2007. "Simulation of pedestrian flow on square lattice based on cellular automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 567-588.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maeno, Yoshiharu, 2011. "Discovery of a missing disease spreader," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3412-3426.
    2. Maeno, Yoshiharu, 2016. "Detecting a trend change in cross-border epidemic transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 73-81.
    3. Maeno, Yoshiharu, 2010. "Discovering network behind infectious disease outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4755-4768.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:389:y:2010:i:3:p:540-548. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.