Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic
Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic
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DOI：
10.1111/insr.12398
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发表时间：
2020-07
影响因子：
2
通讯作者：
J. Loyal;Yuguo Chen
中科院分区：
文献类型：
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作者：
J. Loyal;Yuguo Chen
随着 2019 年冠状病毒病疫情的发展，统计网络分析在为政策决策提供信息方面发挥着重要作用。因此，刚接触此类研究的研究人员需要了解他们可用的技术。作为一个领域，统计网络分析旨在开发能够解释网络数据中复杂依赖关系的方法。在过去的几十年里，该领域迅速积累了方法，包括网络建模和模拟传染病传播的技术。本文回顾了这些网络建模技术及其在 2019 年冠状病毒病大流行中的应用。
As the coronavirus disease 2019 outbreak evolves, statistical network analysis is playing an essential role in informing policy decisions. Therefore, researchers who are new to such studies need to understand the techniques available to them. As a field, statistical network analysis aims to develop methods that account for the complex dependencies found in network data. Over the last few decades, the area has rapidly accumulated methods, including techniques for network modelling and simulating the spread of infectious disease. This article reviews these network modelling techniques and their applications to the coronavirus disease 2019 pandemic.