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首页> 外文期刊>Journal of Mathematical Biology >Mean-field models for non-Markovian epidemics on networks
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Mean-field models for non-Markovian epidemics on networks

机译：网络上非马洛维亚流行病的均值模型

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This paper introduces a novel extension of the edge-based compartmental model to epidemics where the transmission and recovery processes are driven by general independent probability distributions. Edge-based compartmental modelling is just one of many different approaches used to model the spread of an infectious disease on a network; the major result of this paper is the rigorous proof that the edge-based compartmental model and the message passing models are equivalent for general independent transmission and recovery processes. This implies that the new model is exact on the ensemble of configuration model networks of infinite size. For the case of Markovian transmission the message passing model is re-parametrised into a pairwise-like model which is then used to derive many well-known pairwise models for regular networks, or when the infectious period is exponentially distributed or is of a fixed length.
机译：本文介绍了基于边缘的分区模型的新颖延伸，以传输和恢复过程由一般独立概率分布驱动。 基于边缘的隔间建模只是众多不同方法之一，用于模拟网络上传染病的传播; 本文的主要结果是严格的证明，即边缘的隔间模型和消息传递模型是相当于一般独立传输和恢复过程的等效。 这意味着新模型精确在无限大小的配置模型网络的集合上。 对于Markovian传输的情况，将消息传递模型重新参加到类似的配对模型，然后用于衍生常规网络的许多众所周知的成对模型，或者当传染期是指数分布的或者是固定的长度时 。

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