A scoping review of digital twins in the context of the Covid-19 pandemic

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

Customer Interaction in Software Development: A Comparison of Software Methodologies Deployed in Namibian Software Firms

Software methodologies provide guidelines for the development of software applications. Studies reveal that customer interaction in the software development process improves the chances that software applications will meet customers' needs. Despite a number of software methodologies introduced and a comparison of these methodologies, there is a dearth of studies that empirically investigate customer interaction between these software methodologies within the Namibian context. The purpose of this study was to examine the differences in customer interaction between software methodologies deployed in Namibian software firms. The study adopted a qualitative, case study approach. Data was collected through standardized, open-ended interviews. The findings show that the methodologies deployed in Namibian software firms include the waterfall model, Scrum, iterative model, eXtreme Programming (XP), and rapid application development (RAD). The findings also reveal that although there was in-depth customer interaction in Scrum, the iterative model, XP and RAD, customer interaction in the software development process could also be challenging. The findings provide useful insights in software methodologies deployed in Namibian software firms and the experience within the Namibian context. An implication for software project managers and software developers is that customer interaction should be properly managed to ensure that the software methodologies for improving software development processes are effectively deployed