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Interdependency and hierarchy of exact and approximate epidemic models on networks

机译:网络上精确和近似流行病模型的相互依赖性和层次结构

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摘要

Over the years numerous models of SI S (susceptible → infected → susceptible) disease dynamics unfolding on networks have been proposed. Here, we discuss the links between many of these models and how they can be viewed as more general motif-based models. We illustrate how the different models can be derived from one another and, where this is not possible, discuss extensions to established models that enables this derivation. We also derive a general result for the exact differential equations for the expected number of an arbitrary motif directly from the Kolmogorov/master equations and conclude with a comparison of the performance of the different closed systems of equations on networks of varying structure.
机译:多年来,已经提出了在网络上展开的许多SI S(易感→感染→易感)疾病动态模型。在这里,我们讨论了许多这些模型之间的联系,以及如何将它们视为更通用的基于主题的模型。我们说明了如何才能相互推导不同的模型,并在不可能的情况下,讨论了对建立模型的扩展,以实现这种推导。我们还直接从Kolmogorov / master方程中得出了任意主题的预期数量的精确微分方程的一般结果,并得出了在结构变化的网络上不同封闭方程组的性能比较的结论。

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