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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：本文介绍了一种基于边缘的区域模型的新扩展，用于传染病的传播和恢复过程由一般独立的概率分布驱动。基于边缘的分区建模只是用于模拟网络上传染病传播的许多不同方法之一；本文的主要结果是，对于一般的独立传输和恢复过程，基于边缘的划分模型和消息传递模型是等价的。这意味着新模型完全是无限大的配置模型网络的集合。对于马尔可夫传播的情况，将消息传递模型重新参数化为一个类似成对的模型，然后使用该模型导出许多已知的规则网络成对模型，或者当传染期呈指数分布或具有固定长度时。

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