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

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.

Detecting latent topics and trends of digital twins in healthcare: A structural topic model-based systematic review

“… 51 , 52 The emergence of the COVID-19 pandemic further strengthened the public's requests for digital and efficient healthcare, highlighting the importance of remote patient monitoring, virtual consultations, and data-driven decision-making. 32 , 53 , 54 The above factors have made “DT + healthcare” an exciting research area with significant potential to transform healthcare and promote digitalization.…”

“…The pandemic pushed people to explore smart frameworks to avoid infection 54 and deal with the shortage or disturbing confusion of medical resources caused by the surge of COVID-19 patients. 32 The pandemic also promoted the popularity of “AI disease diagnosis (topic 4).” AI disease diagnosis can help mitigate the spread of COVID-19 by reducing human-to-human contact. 23 Furthermore, it eliminates the need for patients to physically visit hospitals, saving them valuable time and ensuring a certain level of privacy protection.…”

“…On the other hand, the papers with “Disease treatment” attribute focus on patients and have clear directions for specific diseases such as cardiovascular disease or COVID-19. 29 – 32 Some papers aim to optimize the allocation of medical resources in hospitals and assist rehabilitation were also labeled with the “Disease treatment” attribute. 33 – 38 Papers with this attribute prefer DT to simulate human organs or the effects of different interventions on organs.…”

Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems

“…This enables the estimation of all uncertainties associated with the predicted output and yields a higher value in cases of insufficient data [68]. These methods are used in medical digital twins to improve their prediction capabilities, guide the timing of interventions, and enable early diagnosis [38,52,68,71,[88][89][90].…”

Digital-Twins-Based Internet of Robotic Things for Remote Health Monitoring of COVID-19 Patients

“…The recent coronavirus disease (COVID-19) pandemic has increased the importance of DTs. DTs systems predict and manage contagious disease outbreaks more efficiently and improve hospital management and healthcare services [14]. Unlike earlier pandemics like middle east respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), COVID-19 has a high and asymptomatic transmission capability.…”