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Fitting parameters of stochastic birth–death models to metapopulation data

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  • zu Dohna, Heinrich
  • Pineda-Krch, Mario

Abstract

Populations that are structured into small local patches are a common feature of ecological and epidemiological systems. Models describing this structure are often referred to as metapopulation models in ecology or household models in epidemiology. Small local populations are subject to demographic stochasticity. Theoretical studies of household disease models without resistant stages (SIS models) have shown that local stochasticity can be ignored for between patch disease transmission if the number of connected patches is large. In that case the distribution of the number of infected individuals per household reaches a stationary distribution described by a birth–death process with a constant immigration term. Here we show how this result, in conjunction with the balancing condition for birth–death processes, provides a framework to estimate demographic parameters from a frequency distribution of local population sizes. The parameter estimation framework is applicable to estimate parameters of disease transmission models as well as metapopulation models.

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  • zu Dohna, Heinrich & Pineda-Krch, Mario, 2010. "Fitting parameters of stochastic birth–death models to metapopulation data," Theoretical Population Biology, Elsevier, vol. 78(2), pages 71-76.
    • Handle: RePEc:eee:thpobi:v:78:y:2010:i:2:p:71-76
    DOI: 10.1016/j.tpb.2010.06.004
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    References listed on IDEAS

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    1. Pineda-Krch, Mario, 2008. "GillespieSSA: Implementing the Gillespie Stochastic Simulation Algorithm in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i12).
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    Cited by:

    1. 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.

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