Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic. (29th July 2020)

• Record Type: Journal Article
• Authors: Loyal, Joshua Daniel; Chen, Yuguo
• Is Part Of: International statistical review. Volume 88:Number 2(2020)
• Page Start: 419
• Page End: 440
• Publication Date: 2020-07-29
• Subjects: COVID‐19 -- network models -- network SEIR model -- social networks; Statistics -- Periodicals; Statistics -- Bibliography -- Periodicals; Statistics -- Bibliography; Statistics -- Periodicals; Statistique; Statistique -- Périodiques; Statistique -- Bibliographie -- Périodiques; Statistique -- Étude et enseignement -- Périodiques; Statistique -- Étude et enseignement -- Bibliographie -- Périodiques; Ressource Internet (Descripteur de forme); Périodique électronique (Descripteur de forme); 519.2
• DOI: 10.1111/insr.12398
• Languages: English
• ISSNs: 0306-7734

Abstract

Summary: 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.