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Efficient methods for studying stochastic disease and population dynamics

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  • 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
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    References listed on IDEAS

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    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.
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    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.

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