Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

中文翻译：

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迈向时态网络上的流行阈值：回顾和未解决的问题

流行病学接触网络模型已成为理解和预测传染病传播的重要工具，因为它们具有参与个体异质性的能力，而异质性可能是特定宿主-病原体系统基本动态的基础。现实世界中的联系网络随着时间的推移而发生的变化同样重要，既独立于病原体的传播又是对病原体传播的响应。这些动态因素在确定疾病是否会在人群中死亡或成为流行病（称为流行阈值）方面起着核心作用。在本文中，我们提供了预测时间接触网络模型的流行阈值的方法的概述，并讨论了尚未探索的领域。