Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis

BackgroundMany countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and...

Full description

Bibliographic Details
Main Authors: Elkhodr, Mahmoud, Mubin, Omar, Iftikhar, Zainab, Masood, Maleeha, Alsinglawi, Belal, Shahid, Suleman, Alnajjar, Fady
Format: Article
Language:English
Published: JMIR Publications 2021-02-01
Series:Journal of Medical Internet Research
Online Access:http://www.jmir.org/2021/2/e23467/
id doaj-a075b27032f944a4a4e140256dab60b7
record_format Article
spelling doaj-a075b27032f944a4a4e140256dab60b72021-04-02T21:36:02ZengJMIR PublicationsJournal of Medical Internet Research1438-88712021-02-01232e2346710.2196/23467Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content AnalysisElkhodr, MahmoudMubin, OmarIftikhar, ZainabMasood, MaleehaAlsinglawi, BelalShahid, SulemanAlnajjar, Fady BackgroundMany countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting. ObjectiveThe goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review. MethodsThis research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed. ResultsThis study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps. ConclusionsThis article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.http://www.jmir.org/2021/2/e23467/
collection DOAJ
language English
format Article
sources DOAJ
author Elkhodr, Mahmoud
Mubin, Omar
Iftikhar, Zainab
Masood, Maleeha
Alsinglawi, Belal
Shahid, Suleman
Alnajjar, Fady
spellingShingle Elkhodr, Mahmoud
Mubin, Omar
Iftikhar, Zainab
Masood, Maleeha
Alsinglawi, Belal
Shahid, Suleman
Alnajjar, Fady
Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
Journal of Medical Internet Research
author_facet Elkhodr, Mahmoud
Mubin, Omar
Iftikhar, Zainab
Masood, Maleeha
Alsinglawi, Belal
Shahid, Suleman
Alnajjar, Fady
author_sort Elkhodr, Mahmoud
title Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
title_short Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
title_full Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
title_fullStr Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
title_full_unstemmed Technology, Privacy, and User Opinions of COVID-19 Mobile Apps for Contact Tracing: Systematic Search and Content Analysis
title_sort technology, privacy, and user opinions of covid-19 mobile apps for contact tracing: systematic search and content analysis
publisher JMIR Publications
series Journal of Medical Internet Research
issn 1438-8871
publishDate 2021-02-01
description BackgroundMany countries across the globe have released their own COVID-19 contact tracing apps. This has resulted in the proliferation of several apps that used a variety of technologies. With the absence of a standardized approach used by the authorities, policy makers, and developers, many of these apps were unique. Therefore, they varied by function and the underlying technology used for contact tracing and infection reporting. ObjectiveThe goal of this study was to analyze most of the COVID-19 contact tracing apps in use today. Beyond investigating the privacy features, design, and implications of these apps, this research examined the underlying technologies used in contact tracing apps. It also attempted to provide some insights into their level of penetration and to gauge their public reception. This research also investigated the data collection, reporting, retention, and destruction procedures used by each of the apps under review. MethodsThis research study evaluated 13 apps corresponding to 10 countries based on the underlying technology used. The inclusion criteria ensured that most COVID-19-declared epicenters (ie, countries) were included in the sample, such as Italy. The evaluated apps also included countries that did relatively well in controlling the outbreak of COVID-19, such as Singapore. Informational and unofficial contact tracing apps were excluded from this study. A total of 30,000 reviews corresponding to the 13 apps were scraped from app store webpages and analyzed. ResultsThis study identified seven distinct technologies used by COVID-19 tracing apps and 13 distinct apps. The United States was reported to have released the most contact tracing apps, followed by Italy. Bluetooth was the most frequently used underlying technology, employed by seven apps, whereas three apps used GPS. The Norwegian, Singaporean, Georgian, and New Zealand apps were among those that collected the most personal information from users, whereas some apps, such as the Swiss app and the Italian (Immuni) app, did not collect any user information. The observed minimum amount of time implemented for most of the apps with regard to data destruction was 14 days, while the Georgian app retained records for 3 years. No significant battery drainage issue was reported for most of the apps. Interestingly, only about 2% of the reviewers expressed concerns about their privacy across all apps. The number and frequency of technical issues reported on the Apple App Store were significantly more than those reported on Google Play; the highest was with the New Zealand app, with 27% of the reviewers reporting technical difficulties (ie, 10% out of 27% scraped reviews reported that the app did not work). The Norwegian, Swiss, and US (PathCheck) apps had the least reported technical issues, sitting at just below 10%. In terms of usability, many apps, such as those from Singapore, Australia, and Switzerland, did not provide the users with an option to sign out from their apps. ConclusionsThis article highlighted the fact that COVID-19 contact tracing apps are still facing many obstacles toward their widespread and public acceptance. The main challenges are related to the technical, usability, and privacy issues or to the requirements reported by some users.
url http://www.jmir.org/2021/2/e23467/
work_keys_str_mv AT elkhodrmahmoud technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT mubinomar technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT iftikharzainab technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT masoodmaleeha technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT alsinglawibelal technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT shahidsuleman technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
AT alnajjarfady technologyprivacyanduseropinionsofcovid19mobileappsforcontacttracingsystematicsearchandcontentanalysis
_version_ 1721545091681615872