Big Data and Cognitive Computing (Oct 2022)

Contact Tracing Strategies for COVID-19 Prevention and Containment: A Scoping Review

  • Bolanle Adefowoke Ojokoh,
  • Benjamin Aribisala,
  • Oluwafemi A. Sarumi,
  • Arome Junior Gabriel,
  • Olatunji Omisore,
  • Abiola Ezekiel Taiwo,
  • Tobore Igbe,
  • Uchechukwu Madukaku Chukwuocha,
  • Tunde Yusuf,
  • Abimbola Afolayan,
  • Olusola Babalola,
  • Tolulope Adebayo,
  • Olaitan Afolabi

DOI
https://doi.org/10.3390/bdcc6040111
Journal volume & issue
Vol. 6, no. 4
p. 111

Abstract

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Coronavirus Disease 2019 (COVID-19) spreads rapidly and is easily contracted by individuals who come near infected persons. With this nature and rapid spread of the contagion, different types of research have been conducted to investigate how non-pharmaceutical interventions can be employed to contain and prevent COVID-19. In this review, we analyzed the key elements of digital contact tracing strategies developed for the prevention and containment of the dreaded epidemic since its outbreak. We carried out a scoping review through relevant studies indexed in three databases, namely Google Scholar, PubMed, and ACM Digital Library. Using some carefully defined search terms, a total of 768 articles were identified. The review shows that 86.32% (n = 101) of the works focusing on contact tracing were published in 2020, suggesting there was an increased awareness that year, increased research efforts, and the fact that the pandemic was given a very high priority by most journals. We observed that many (47.86%, n = 56) of the studies were focused on design and implementation issues in the development of COVID-19 contact tracing systems. In addition, has been established that most of the studies were conducted in 41 countries and that contract tracing app development are characterized by some sensitive issues, including privacy-preserving and case-based referral characteristics.

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