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Article Dans Une Revue IEEE Pervasive Computing Année : 2023

Toward Deep Digital Contact Tracing: Opportunities and Challenges

Résumé

During the COVID-19 pandemic, digital contact tracing using mobile devices has been widely explored, with many proposals from academia and industry highlighting the benefits and challenges. Most approaches use Bluetooth low energy signals to learn and trace close contacts among users. However, tracing only these contacts can mask the risk of virus exposure in scenarios with low detection rates. To address this issue, we propose fostering users to exchange information beyond close contacts, particularly about prior "deep" contacts that may have transmitted the virus. This presents new opportunities for controlling the spread of the virus, but also poses challenges that require further investigation. We provide directions for addressing these challenges based on our recent work developing a technological solution using this approach. Risk Analysis Beyond Close Contacts While user privacy has been a major focus in developing DCT solutions, the importance of risk analysis has not received as much attention. Currently, most DCT
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Dates et versions

hal-04282277 , version 1 (14-11-2023)

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Renato Cherini, Ramiro Detke, Juan Fraire, Pablo G Madoery, Jorge M Finochietto. Toward Deep Digital Contact Tracing: Opportunities and Challenges. IEEE Pervasive Computing, 2023, pp.1-11. ⟨10.1109/MPRV.2023.3320987⟩. ⟨hal-04282277⟩
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