IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v389y2010i21p4755-4768.html
   My bibliography  Save this article

Discovering network behind infectious disease outbreak

Author

Listed:
  • Maeno, Yoshiharu

Abstract

Stochasticity and spatial heterogeneity are of great interest recently in studying the spread of an infectious disease. The presented method solves an inverse problem to discover the effectively decisive topology of a heterogeneous network and reveal the transmission parameters which govern the stochastic spreads over the network from a dataset on an infectious disease outbreak in the early growth phase. Populations in a combination of epidemiological compartment models and a meta-population network model are described by stochastic differential equations. Probability density functions are derived from the equations and used for the maximal likelihood estimation of the topology and parameters. The method is tested with computationally synthesized datasets and the WHO dataset on the SARS outbreak.

Suggested Citation

  • Maeno, Yoshiharu, 2010. "Discovering network behind infectious disease outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 4755-4768.
    • Handle: RePEc:eee:phsmap:v:389:y:2010:i:21:p:4755-4768
    DOI: 10.1016/j.physa.2010.07.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437110006412
    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
    File URL: https://libkey.io/10.1016/j.physa.2010.07.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. 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.
    2. Fujie, Ryo & Odagaki, Takashi, 2007. "Effects of superspreaders in spread of epidemic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(2), pages 843-852.
    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. Yoshiharu Maeno & Kenji Nishiguchi & Satoshi Morinaga & Hirokazu Matsushima, 2014. "Impact of credit default swaps on financial contagion," Papers 1411.1356, arXiv.org.
    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, 2013. "Transient fluctuation of the prosperity of firms in a network economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3351-3359.
    4. Yoshiharu Maeno & Satoshi Morinaga & Hirokazu Matsushima & Kenichi Amagai, 2012. "Transmission of distress in a bank credit network," Papers 1204.5661, arXiv.org, revised Nov 2012.
    5. Maeno, Yoshiharu, 2011. "Discovery of a missing disease spreader," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3412-3426.
    6. Yoshiharu Maeno & Kenji Nishiguchi & Satoshi Morinaga & Hirokazu Matsushima, 2012. "Optimal portfolio for a robust financial system," Papers 1211.5235, arXiv.org, revised Feb 2013.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Yunhwan Kim & Hohyung Ryu & Sunmi Lee, 2018. "Agent-Based Modeling for Super-Spreading Events: A Case Study of MERS-CoV Transmission Dynamics in the Republic of Korea," IJERPH, MDPI, vol. 15(11), pages 1-17, October.
    3. 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.

    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:21:p:4755-4768. See general information about how to correct material in RePEc.

    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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.

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

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.