Literature DB >> 33551673

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment.

Mirco Nanni1, Gennady Andrienko2,3, Albert-László Barabási4, Chiara Boldrini5, Francesco Bonchi6,7, Ciro Cattuto6,8, Francesca Chiaromonte9,10, Giovanni Comandé9, Marco Conti5, Mark Coté11, Frank Dignum12, Virginia Dignum12, Josep Domingo-Ferrer13, Paolo Ferragina14, Fosca Giannotti1, Riccardo Guidotti14, Dirk Helbing15, Kimmo Kaski16, Janos Kertesz17, Sune Lehmann18, Bruno Lepri19, Paul Lukowicz20, Stan Matwin21,22, David Megías Jiménez23, Anna Monreale14, Katharina Morik24, Nuria Oliver25,26, Andrea Passarella5, Andrea Passerini27, Dino Pedreschi14, Alex Pentland28, Fabio Pianesi29, Francesca Pratesi14, Salvatore Rinzivillo1, Salvatore Ruggieri14, Arno Siebes30, Vicenc Torra12,31, Roberto Trasarti1, Jeroen van den Hoven32, Alessandro Vespignani4.   

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outbreaks, especially in the "phase 2" of the pandemic, when lockdown and other restriction measures are progressively withdrawn, in order to avoid or minimize contagion resurgence.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 for COVID-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 allow the user to share spatio-temporal aggregates-if and when they want and for specific aims-with health authorities, for instance. Second, we favour a longer-term 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.
© The Author(s) 2021.

Entities:  

Keywords:  COVID-19; Contact tracing; Mobility data analysis; Personal data store

Year:  2021        PMID: 33551673      PMCID: PMC7851322          DOI: 10.1007/s10676-020-09572-w

Source DB:  PubMed          Journal:  Ethics Inf Technol        ISSN: 1388-1957


  4 in total

1.  South Korea is reporting intimate details of COVID-19 cases: has it helped?

Authors:  Mark Zastrow
Journal:  Nature       Date:  2020-03-18       Impact factor: 49.962

2.  openPDS: protecting the privacy of metadata through SafeAnswers.

Authors:  Yves-Alexandre de Montjoye; Erez Shmueli; Samuel S Wang; Alex Sandy Pentland
Journal:  PLoS One       Date:  2014-07-09       Impact factor: 3.240

3.  Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1.

Authors:  Neeltje van Doremalen; Trenton Bushmaker; Dylan H Morris; Myndi G Holbrook; Amandine Gamble; Brandi N Williamson; Azaibi Tamin; Jennifer L Harcourt; Natalie J Thornburg; Susan I Gerber; James O Lloyd-Smith; Emmie de Wit; Vincent J Munster
Journal:  N Engl J Med       Date:  2020-03-17       Impact factor: 91.245

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

Authors:  Luca Ferretti; Chris Wymant; David Bonsall; Christophe Fraser; Michelle Kendall; Lele Zhao; Anel Nurtay; Lucie Abeler-Dörner; Michael Parker
Journal:  Science       Date:  2020-03-31       Impact factor: 47.728

  4 in total
  3 in total

Review 1.  How is "solidarity" understood in discussions about contact tracing apps? An overview.

Authors:  Max Tretter
Journal:  Front Public Health       Date:  2022-07-22

Review 2.  Data-driven methods for present and future pandemics: Monitoring, modelling and managing.

Authors:  Teodoro Alamo; Daniel G Reina; Pablo Millán Gata; Victor M Preciado; Giulia Giordano
Journal:  Annu Rev Control       Date:  2021-06-29       Impact factor: 6.091

3.  Data privacy during pandemics: a systematic literature review of COVID-19 smartphone applications.

Authors:  Amany Alshawi; Muna Al-Razgan; Fatima H AlKallas; Raghad Abdullah Bin Suhaim; Reem Al-Tamimi; Norah Alharbi; Sarah Omar AlSaif
Journal:  PeerJ Comput Sci       Date:  2022-01-04
  3 in total

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