Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
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Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Date
2020-04-01
Department
National Research Council of Italy
Fraunhofer Institute for Intelligent Analysis and Information Systems
Northeastern University
IIT-CNR
ISI Foundation
Sant'Anna School of Advanced Studies
King's College London
Umeå University
Universidad Rovira i Virgili
University of Pisa
Swiss Federal Institute of Technology Zurich
Kaski Kimmo group
Central European University
Danmarks Tekniske Universitet
Fondazione Bruno Kessler
German Research Center for Artificial Intelligence (DFKI)
Dalhousie University
Open University of Catalonia
TU Dortmund University
ELLIS Alicante
Università degli Studi di Trento
Massachusetts Institute of Technology MIT
EIT Digital
Utrecht University
Maynooth University
Delft University of Technology
Department of Computer Science
Fraunhofer Institute for Intelligent Analysis and Information Systems
Northeastern University
IIT-CNR
ISI Foundation
Sant'Anna School of Advanced Studies
King's College London
Umeå University
Universidad Rovira i Virgili
University of Pisa
Swiss Federal Institute of Technology Zurich
Kaski Kimmo group
Central European University
Danmarks Tekniske Universitet
Fondazione Bruno Kessler
German Research Center for Artificial Intelligence (DFKI)
Dalhousie University
Open University of Catalonia
TU Dortmund University
ELLIS Alicante
Università degli Studi di Trento
Massachusetts Institute of Technology MIT
EIT Digital
Utrecht University
Maynooth University
Delft University of Technology
Department of Computer Science
Major/Subject
Mcode
Degree programme
Language
en
Pages
6
61-66
61-66
Series
Transactions on data privacy, Volume 13, issue 1
Abstract
The rapid dynamics of COVID-19 calls for quick and effective tracking of virus transmission chains and early detection of outbreaks, especially in the “phase 2” of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence. For this purpose, contact-tracing apps are being proposed for large scale adoption by many countries. A centralized approach, where data sensed by the app are all sent to a nation-wide server, raises concerns about citizens’ privacy and needlessly strong digital surveillance, thus alerting us to the need to minimize personal data collection and avoiding location tracking. We advocate the conceptual advantage of a decentralized approach, where both contact and location data are collected exclusively in individual citizens’ “personal data stores”, to be shared separately and selectively (e.g., with a backend system, but possibly also with other citizens), voluntarily, only when the citizen has tested positive forCOVID-19, and with a privacy preserving level of granularity. This approach better protects the personal sphere of citizens and affords multiple benefits: It allows for detailed information gathering for infected people in a privacy-preserving fashion; and, in turn this enables both contact tracing, and, the early detection of outbreak hotspots on more finely-granulated geographic scale. The decentralized approach is also scalable to large populations, in that only the data of positive patients need be handled at a central level. Our recommendation is two-fold. First to extend existing decentralized architectures with a light touch, in order to manage the collection of location data locally on the device, and allowthe user to share spatio-temporal aggregates-if and when they want and for specific aims-with health authorities, for instance. Second, we favour a longerterm pursuit of realizing a Personal Data Store vision, giving users the opportunity to contribute to collective good in the measure they want, enhancing self-awareness, and cultivating collective efforts for rebuilding society.Description
Keywords
Contact tracing, COVID-19, Mobility data analysis, Personal Data Store
Other note
Citation
Nanni , M , Andrienko , G , Barabàsi , A L , Boldrini , C , Bonchi , F , Cattuto , C , Chiaromonte , F , Comandé , G , Conti , M , Coté , M , Dignum , F , Dignum , V , Domingo-Ferrer , J , Ferragina , P , Giannotti , F , Guidotti , R , Helbing , D , Kaski , K , Kertesz , J , Lehmann , S , Lepri , B , Lukowicz , P , Matwin , S , Jiménez , D , Monreale , A , Morik , K , Oliver , N , Passarella , A , Passerini , A , Pedreschi , D , Pentland , A , Pianesi , F , Pratesi , F , Rinzivillo , S , Ruggieri , S , Siebes , A , Torra , V , Trasarti , R , Van Den Hoven , J & Vespignani , A 2020 , ' Give more data, awareness and control to individual citizens, and they will help COVID-19 containment ' , Transactions on data privacy , vol. 13 , no. 1 , pp. 61-66 . < https://arxiv.org/abs/2004.05222 >