A critical review of emerging technologies for tackling COVID‐19 pandemic. Issue 1 (1st December 2020)

• Record Type: Journal Article
• Authors: Mbunge, Elliot; Akinnuwesi, Boluwaji; Fashoto, Stephen G.; Metfula, Andile S.; Mashwama, Petros
• Is Part Of: Human behavior and emerging technologies. Volume 3:Issue 1(2021)
• Page Start: 25
• Page End: 39
• Publication Date: 2020-12-01
• Subjects: contact tracing -- COVID‐19 -- diagnoses -- emerging technology -- pandemic -- screening -- surveillance -- tracking; Human behavior -- Periodicals; Technological innovations -- Social aspects -- Periodicals; Human-computer interaction -- Periodicals; 303.48305
• DOI: 10.1002/hbe2.237
• Languages: English
• ISSNs: 2578-1863

Abstract

Abstract: COVID‐19 pandemic affects people in various ways and continues to spread globally. Researches are ongoing to develop vaccines and traditional methods of Medicine and Biology have been applied in diagnosis and treatment. Though there are success stories of recovered cases as of November 10, 2020, there are no approved treatments and vaccines for COVID‐19. As the pandemic continues to spread, current measures rely on prevention, surveillance, and containment. In light of this, emerging technologies for tackling COVID‐19 become inevitable. Emerging technologies including geospatial technology, artificial intelligence (AI), big data, telemedicine, blockchain, 5G technology, smart applications, Internet of Medical Things (IoMT), robotics, and additive manufacturing are substantially important for COVID‐19 detecting, monitoring, diagnosing, screening, surveillance, mapping, tracking, and creating awareness. Therefore, this study aimed at providing a comprehensive review of these technologies for tackling COVID‐19 with emphasis on the features, challenges, and country of domiciliation. Our results show that performance of the emerging technologies is not yet stable due to nonavailability of enough COVID‐19 dataset, inconsistency in some of the dataset available, nonaggregation of the dataset due to contrasting data format, missing data, and noise. Moreover, the security and privacy of people's health information is not totally guaranteed. Thus, further research is required to strengthen the current technologies and there is a strong need for the emergence of a robust computationally intelligent model for early differential diagnosis of COVID‐19.