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

COVID-19 Contact tracing Location privacy Mobile application Privacy Privacy protection

Journal

PeerJ. Computer science
ISSN: 2376-5992
Titre abrégé: PeerJ Comput Sci
Pays: United States
ID NLM: 101660598

Informations de publication

Date de publication:
2022
Historique:
received: 16 08 2021
accepted: 01 12 2021
entrez: 3 2 2022
pubmed: 4 2 2022
medline: 4 2 2022
Statut: epublish

Résumé

On January 8, 2020, the Centers for Disease Control and Prevention officially announced a new virus in Wuhan, China. The first novel coronavirus (COVID-19) case was discovered on December 1, 2019, implying that the disease was spreading quietly and quickly in the community before reaching the rest of the world. To deal with the virus' wide spread, countries have deployed contact tracing mobile applications to control viral transmission. Such applications collect users' information and inform them if they were in contact with an individual diagnosed with COVID-19. However, these applications might have affected human rights by breaching users' privacy. This systematic literature review followed a comprehensive methodology to highlight current research discussing such privacy issues. First, it used a search strategy to obtain 808 relevant papers published in 2020 from well-established digital libraries. Second, inclusion/exclusion criteria and the snowballing technique were applied to produce more comprehensive results. Finally, by the application of a quality assessment procedure, 40 studies were chosen. This review highlights privacy issues, discusses centralized and decentralized models and the different technologies affecting users' privacy, and identifies solutions to improve data privacy from three perspectives: public, law, and health considerations. Governments need to address the privacy issues related to contact tracing apps. This can be done through enforcing special policies to guarantee users privacy. Additionally, it is important to be transparent and let users know what data is being collected and how it is being used.

Sections du résumé

BACKGROUND BACKGROUND
On January 8, 2020, the Centers for Disease Control and Prevention officially announced a new virus in Wuhan, China. The first novel coronavirus (COVID-19) case was discovered on December 1, 2019, implying that the disease was spreading quietly and quickly in the community before reaching the rest of the world. To deal with the virus' wide spread, countries have deployed contact tracing mobile applications to control viral transmission. Such applications collect users' information and inform them if they were in contact with an individual diagnosed with COVID-19. However, these applications might have affected human rights by breaching users' privacy.
METHODOLOGY METHODS
This systematic literature review followed a comprehensive methodology to highlight current research discussing such privacy issues. First, it used a search strategy to obtain 808 relevant papers published in 2020 from well-established digital libraries. Second, inclusion/exclusion criteria and the snowballing technique were applied to produce more comprehensive results. Finally, by the application of a quality assessment procedure, 40 studies were chosen.
RESULTS RESULTS
This review highlights privacy issues, discusses centralized and decentralized models and the different technologies affecting users' privacy, and identifies solutions to improve data privacy from three perspectives: public, law, and health considerations.
CONCLUSIONS CONCLUSIONS
Governments need to address the privacy issues related to contact tracing apps. This can be done through enforcing special policies to guarantee users privacy. Additionally, it is important to be transparent and let users know what data is being collected and how it is being used.

Identifiants

pubmed: 35111915
doi: 10.7717/peerj-cs.826
pii: cs-826
pmc: PMC8771796
doi:

Types de publication

Journal Article

Langues

eng

Pagination

e826

Informations de copyright

© 2022 Alshawi et al.

Déclaration de conflit d'intérêts

The authors declare that they have no competing interests.

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Auteurs

Amany Alshawi (A)

King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia.

Muna Al-Razgan (M)

King Saud University (KSU), Riyad, Saudi Arabia.

Fatima H AlKallas (FH)

King Saud University (KSU), Riyad, Saudi Arabia.

Raghad Abdullah Bin Suhaim (RA)

King Saud University (KSU), Riyad, Saudi Arabia.

Reem Al-Tamimi (R)

King Saud University (KSU), Riyad, Saudi Arabia.

Norah Alharbi (N)

King Saud University (KSU), Riyad, Saudi Arabia.

Sarah Omar AlSaif (SO)

King Saud University (KSU), Riyad, Saudi Arabia.

Classifications MeSH