Premium
Statistical Network Analysis: A Review with Applications to the Coronavirus Disease 2019 Pandemic
Author(s) -
Loyal Joshua Daniel,
Chen Yuguo
Publication year - 2020
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/insr.12398
Subject(s) - pandemic , coronavirus , network analysis , covid-19 , computer science , data science , statistical analysis , outbreak , infectious disease (medical specialty) , field (mathematics) , disease , operations research , virology , statistics , medicine , engineering , mathematics , pathology , pure mathematics , electrical engineering
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.