Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic

Joshua Daniel Loyal, Yuguo Chen

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)419-440
Number of pages22
JournalInternational Statistical Review
Volume88
Issue number2
DOIs
StatePublished - Aug 1 2020

Keywords

  • COVID-19
  • network SEIR model
  • network models
  • social networks

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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