Digital Contact Tracing: Large-Scale Geolocation Data as an Alternative to Bluetooth-Based Apps Failure

Author:

González-Cabañas JoséORCID,Cuevas ÁngelORCID,Cuevas RubénORCID,Maier MartinORCID

Abstract

The currently deployed contact-tracing mobile apps have failed as an efficient solution in the context of the COVID-19 pandemic. None of them have managed to attract the number of active users required to achieve efficient operation. This urges the research community to re-open the debate and explore new avenues to lead to efficient contact-tracing solutions. In this paper, we contribute to this debate with an alternative contact-tracing solution that leverages the already available geolocation information owned by BigTech companies that have large penetration rates in most of the countries adopting contact-tracing mobile apps. Our solution provides sufficient privacy guarantees to protect the identity of infected users as well as to preclude Health Authorities from obtaining the contact graph from individuals.

Funder

H2020 LEIT Information and Communication Technologies

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Ministerio de Educación, Cultura y Deporte

Ministerio de Ciencia e Innovación

Comunidad de Madrid

Fundación BBVA

Natural Sciences and Engineering Research Council of Canada

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference38 articles.

1. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing

2. Call for More People to Use Contact-Tracing Apphttps://www.straitstimes.com/singapore/call-for-more-people-to-use-contact-tracing-app

3. Effective Configurations of a Digital Contact Tracing App: A Report to NHSXhttps://github.com/BDI-pathogens/covid-19_instant_tracing/blob/master/Report

4. Decentralized Privacy-Preserving Proximity Tracing;Troncoso;arXiv,2020

5. Without a trace: Why did corona apps fail?

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