IDEAS home Printed from https://ideas.repec.org/a/taf/mpopst/v14y2007i4p237-267.html
   My bibliography  Save this article

Influence of Selected Formation Rules for Finite Population Networks with Fixed Macrostructures: Implications for Individual-Based Model of Infectious Diseases

Author

Listed:
  • M. C. BOILY
  • Z. ASGHAR
  • T. GARSKE
  • A. C. GHANI
  • R. POULIN

Abstract

Individual-based network models are increasingly being applied to understand the transmission dynamics of infectious diseases. Research in this area has mostly focused on networks defined under a limited set of rules (e.g., preferential attachment, sexual partner formation and dissolution) that are supposed to mimic the real world but are often defined heuristically due to lack of empirical knowledge. Here, two different mechanisms ( M- and λ 2 -rules) were used to generate a wide range of networks and to show the extent to which microstructures such as the mean component size, the size of the giant component and the cumulative nomination centrality index may vary between networks with fixed predetermined macrostructure characteristics (size, node degree distribution and mixing pattern) and influence disease transmission. It is important to carefully consider the limitations of network models and to appreciate the extent to which a given degree distribution and mixing pattern will be consistent with a wide range of underlying network microstructures.

Suggested Citation

  • M. C. Boily & Z. Asghar & T. Garske & A. C. Ghani & R. Poulin, 2007. "Influence of Selected Formation Rules for Finite Population Networks with Fixed Macrostructures: Implications for Individual-Based Model of Infectious Diseases," Mathematical Population Studies, Taylor & Francis Journals, vol. 14(4), pages 237-267, November.
    • Handle: RePEc:taf:mpopst:v:14:y:2007:i:4:p:237-267
    DOI: 10.1080/08898480701612873
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/08898480701612873
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/08898480701612873?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.

    Citations

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


    Cited by:

    1. Jenny Lennartsson & Nina Håkansson & Uno Wennergren & Annie Jonsson, 2012. "SpecNet: A Spatial Network Algorithm that Generates a Wide Range of Specific Structures," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    2. Duncan, A.J. & Gunn, G.J. & Umstatter, C. & Humphry, R.W., 2014. "Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks," Theoretical Population Biology, Elsevier, vol. 98(C), pages 11-18.

    More about this item

    Statistics

    Access and download statistics

    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:taf:mpopst:v:14:y:2007:i:4:p:237-267. 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.

    We have no bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GMPS20 .

    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.