IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v75y2009i2p133-141.html
   My bibliography  Save this article

Efficient methods for studying stochastic disease and population dynamics

Author

Listed:
  • Keeling, M.J.
  • Ross, J.V.

Abstract

Stochastic ecological and epidemiological models are now routinely used to inform management and decision making throughout conservation and public-health. A difficulty with the use of such models is the need to resort to simulation methods when the population size (and hence the size of the state space) becomes large, resulting in the need for a large amount of computation to achieve statistical confidence in results. Here we present two methods that allow evaluation of all quantities associated with one- (and higher) dimensional Markov processes with large state spaces. We illustrate these methods using SIS disease dynamics and studying species that are affected by catastrophic events. The methods allow the possibility of extending exact Markov methods to real-world problems, providing techniques for efficient parameterisation and subsequent analysis.

Suggested Citation

  • Keeling, M.J. & Ross, J.V., 2009. "Efficient methods for studying stochastic disease and population dynamics," Theoretical Population Biology, Elsevier, vol. 75(2), pages 133-141.
    • Handle: RePEc:eee:thpobi:v:75:y:2009:i:2:p:133-141
    DOI: 10.1016/j.tpb.2009.01.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580909000124
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2009.01.003?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. Cairns, B.J. & Ross, J.V. & Taimre, T., 2007. "A comparison of models for predicting population persistence," Ecological Modelling, Elsevier, vol. 201(1), pages 19-26.
    2. Ross, J.V. & Pollett, P.K., 2007. "On costs and decisions in population management," Ecological Modelling, Elsevier, vol. 201(1), pages 60-66.
    3. Ross, J.V. & Pagendam, D.E. & Pollett, P.K., 2009. "On parameter estimation in population models II: Multi-dimensional processes and transient dynamics," Theoretical Population Biology, Elsevier, vol. 75(2), pages 123-132.
    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. Sharkey, Kieran J., 2011. "Deterministic epidemic models on contact networks: Correlations and unbiological terms," Theoretical Population Biology, Elsevier, vol. 79(4), pages 115-129.

    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. Rebuli, Nicolas P. & Bean, N.G. & Ross, J.V., 2018. "Estimating the basic reproductive number during the early stages of an emerging epidemic," Theoretical Population Biology, Elsevier, vol. 119(C), pages 26-36.
    2. Christian H. Weiß & Philip K. Pollett, 2012. "Chain Binomial Models and Binomial Autoregressive Processes," Biometrics, The International Biometric Society, vol. 68(3), pages 815-824, September.
    3. Artalejo, J.R. & Lopez-Herrero, M.J., 2011. "The SIS and SIR stochastic epidemic models: A maximum entropy approach," Theoretical Population Biology, Elsevier, vol. 80(4), pages 256-264.
    4. Bown, James L. & Pachepsky, Elizaveta & Eberst, Alistair & Bausenwein, Ursula & Millard, Peter & Squire, Geoff R. & Crawford, John W., 2007. "Consequences of intraspecific variation for the structure and function of ecological communities," Ecological Modelling, Elsevier, vol. 207(2), pages 264-276.
    5. Campillo, F. & Joannides, M. & Larramendy-Valverde, I., 2011. "Stochastic modeling of the chemostat," Ecological Modelling, Elsevier, vol. 222(15), pages 2676-2689.
    6. Ross, J.V., 2012. "On parameter estimation in population models III: Time-inhomogeneous processes and observation error," Theoretical Population Biology, Elsevier, vol. 82(1), pages 1-17.
    7. Jonathan Fintzi & Jon Wakefield & Vladimir N. Minin, 2022. "A linear noise approximation for stochastic epidemic models fit to partially observed incidence counts," Biometrics, The International Biometric Society, vol. 78(4), pages 1530-1541, December.

    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:thpobi:v:75:y:2009:i:2:p:133-141. 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: https://www.journals.elsevier.com/intelligence .

    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.