The role of AI in digital contact tracing

Sofiane Abbar, Mohamed Mokbel

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


With a pandemic widespread and a worldwide lockdown, causing an unprecedented economic crisis, contact tracing is identified by WHO, CDC, and many other government health institutions as a must for pandemic control. The EU Commission, for instance, recommends that contact tracing is needed for people to return to hotels and camping sites. In the USA, several states have made contact tracing a prerequisite for reopening, including California, Pennsylvania, and Virginia, to name a few. Motivated by the limitations of human contact tracing, several governments have partnered with the IT industry such as telecommunication companies and tech giants such as Apple and Google to deploy digital contact-tracing solutions. The result is several approaches and hundreds of mobile contact-tracing apps available on different app stores. In this chapter, we will depict the backbone of digital contract-tracing solutions. We will show that despite the variety of proposals and applications, existing contact-tracing solutions revolve around two main approaches: (1) proximity-based contact tracing using Bluetooth and (2) location-based contact tracing, which relies on localization technologies such as global positioning system, call data record, and WiFi. We will also discuss the advantages and limitations of each approach, their privacy implications, and finally the role of artificial intelligence in improving their efficiency.

Original languageEnglish (US)
Title of host publicationLeveraging Artificial Intelligence in Global Epidemics
Number of pages19
ISBN (Electronic)9780323897778
StatePublished - Jan 1 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Inc. All rights reserved.


  • Contact tracing
  • Location-based services
  • Proximity analysis
  • Spatial computing
  • Spatiotemporal data
  • Trajectory analysis


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