Evidence map›Paper›PMID 33363278›Full record

ReviewHuman behavior and emerging technologies2021

A critical review of emerging technologies for tackling COVID-19 pandemic.

Elliot Mbunge, Boluwaji Akinnuwesi, Stephen G Fashoto, Andile S Metfula, Petros Mashwama

Open access · bronzeAbstract readReview
In one paragraph

Review in Human behavior and emerging technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 2 pooled it
16.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 2 syntheses or guidelines pooled it, 187 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Over time analysis of the codon usage of SARS-CoV-2 and its variants.Computational and structural biotechnology journal · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Which decisions affect cohort distribution in COVID-19 data analytics?AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024
    Article
  14. Article
  15. Article
  16. Article
  17. Understanding the Link between COVID-19 and HIV/AIDS Stigmas.Journal of applied social science · 2023
    Article
  18. Review
  19. Characteristics and specifications of dashboards developed for the COVID-19 pandemic: a scoping review.Zeitschrift fur Gesundheitswissenschaften = Journal of public health · 2023
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

Elliot MbungeDepartment of Computer Science, Faculty of Science and Engineering University of Eswatini Manzini Swaziland.ORCID https://orcid.org/0000-0003-4504-6697
Boluwaji AkinnuwesiDepartment of Computer Science, Faculty of Science and Engineering University of Eswatini Manzini Swaziland.
Stephen G FashotoDepartment of Computer Science, Faculty of Science and Engineering University of Eswatini Manzini Swaziland.
Andile S MetfulaDepartment of Computer Science, Faculty of Science and Engineering University of Eswatini Manzini Swaziland.
Petros MashwamaDepartment of Computer Science, Faculty of Science and Engineering University of Eswatini Manzini Swaziland.
University of Eswatini · SZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

contact tracingCOVID‐19diagnosesemerging technologypandemicscreeningsurveillancetracking

Identifiers

PMID33363278
PMCPMC7753602
OpenAlexW3108908728

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.