A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic

Asiya Khan; Madison Milne-Ives; Edward Meinert; Gloria E Iyawa; Ray B Jones; Alex N Josephraj

doi:10.1177/11795972221102115

A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic

Biomed Eng Comput Biol. 2022 May 24:13:11795972221102115. doi: 10.1177/11795972221102115. eCollection 2022.

Authors

Asiya Khan¹, Madison Milne-Ives², Edward Meinert^{2

3}, Gloria E Iyawa⁴, Ray B Jones², Alex N Josephraj⁵

Affiliations

¹ School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth, UK.
² Centre for Health Technology, University of Plymouth, Plymouth, UK.
³ Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, UK.
⁴ Department of Computing, Sheffield Hallam University, Sheffield, UK.
⁵ Key Laboratory of Digital Signal and Image Processing of Guandong Province, Shantou University, Shantou, China.

Abstract

Background: Digital Twins (DTs), virtual copies of physical entities, are a promising tool to help manage and predict outbreaks of Covid-19. By providing a detailed model of each patient, DTs can be used to determine what method of care will be most effective for that individual. The improvement in patient experience and care delivery will help to reduce demand on healthcare services and to improve hospital management.

Objectives: The aim of this study is to address 2 research questions: (1) How effective are DTs in predicting and managing infectious diseases such as Covid-19? and (2) What are the prospects and challenges associated with the use of DTs in healthcare?

Methods: The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) framework. Titles and abstracts of references in PubMed, IEEE Xplore, Scopus, ScienceDirect and Google Scholar were searched using selected keywords (relating to digital twins, healthcare and Covid-19). The papers were screened in accordance with the inclusion and exclusion criteria so that all papers published in English relating to the use of digital twins in healthcare were included. A narrative synthesis was used to analyse the included papers.

Results: Eighteen papers met the inclusion criteria and were included in the review. None of the included papers examined the use of DTs in the context of Covid-19, or infectious disease outbreaks in general. Academic research about the applications, opportunities and challenges of DT technology in healthcare in general was found to be in early stages.

Conclusions: The review identifies a need for further research into the use of DTs in healthcare, particularly in the context of infectious disease outbreaks. Based on frameworks identified during the review, this paper presents a preliminary conceptual framework for the use of DTs for hospital management during the Covid-19 outbreak to address this research gap.

Keywords: Covid-19; Digital Twins; disease outbreaks; healthcare; public health.

Publication types

Review