Scrutinising COVIDSafe: Frameworks for evaluating digital contact tracing technologies

Lodders, Adam; Paterson, Jeannie Marie

doi:10.1177/1037969x20948262

Cited by 21 publications

(15 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Data security concerns, namely lack of privacy and fearing the normalization of governmental tracking; functionality issues, in particular negative impact on phone performance through increased battery usage; and privacy considerations due to the need for a centralized database, which is an integral design feature of tracing applications based on the centralized approach, were identified early as a potential barrier for acceptance of the COVIDSafe app. (19)(20)(21)(22)(23) Second, with a positive predictive value below 40% and an estimated sensitivity of 15%, the diagnostic performance of the app was not sufficiently high to add value for COVID-19 contact tracing in NSW. Given that the app is intended to complement rather than to replace conventional contact tracing, a modest sensitivity might have been acceptable, particularly since some exposure settings were judged to be high risk and broader close contact criteria were applied.…”

Section: Resultsmentioning

confidence: 96%

Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia

Vogt

Haire

Selvey

et al. 2021

Preprint

View full text Add to dashboard Cite

BackgroundDigital proximity tracing applications were rolled out early in the COVID-19 pandemic in many countries to complement conventional contact tracing. Empirical evidence about their benefits for pandemic response remains scarce. We evaluated the effectiveness and usefulness of ‘COVIDSafe’, Australia’s national smartphone-based proximity tracing application for COVID-19.MethodsIn this prospective study, conducted in New South Wales, Australia between May and November 2020, we calculated the positive predictive value and sensitivity of COVIDSafe, its additional contact yield, and the number of averted public exposure events. Semi-structured interviews with public health staff were conducted to assess the application’s usefulness.ResultsThere were 619 confirmed COVID-19 cases and over 25,300 close contacts during the study period. COVIDSafe was used by 137 (22%) cases and detected 79 (0·3%) close contacts. It had a positive predictive value of 39% and a sensitivity of 15%, and detected 17 (0·07%) additional close contacts that were not identified by conventional contact tracing. The application generated a substantial additional workload for public health staff and was not considered useful.ConclusionsCOVIDSafe was not sufficiently effective to make a meaningful contribution to the COVID-19 response in Australia’s most populous state over a 6-month period. This contrasts optimistic projections from modelling studies about the added value of digitally supported contact tracing. We found no evidence that it adds value to conventional contact tracing, and recommend that their implementation should always include comprehensive effectiveness evaluations.

show abstract

Section: Resultsmentioning

confidence: 96%

Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia

Vogt

Haire

Selvey

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

“…There are cases in which governments receiving personal data must be identified. All population groups should be able to use COVID-19 surveillance technology which respects their privacy ( Lodders & Paterson, 2020 ; Van Kolfschooten & de Ruijter, 2020 ; Lee & Lee, 2020 ). The use of the contact-tracing process is unprecedented and could have serious consequences for public health.…”

Section: Discussionmentioning

confidence: 99%

“…The use of the contact-tracing process is unprecedented and could have serious consequences for public health. It is necessary to implement public-interest digital technology practices that are in line with values ( Lodders & Paterson, 2020 ; Van Kolfschooten & de Ruijter, 2020 ; Lee & Lee, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

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

Alshawi

Al-Razgan

Alkallas

et al. 2022

PeerJ Computer Science

View full text Add to dashboard Cite

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 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 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 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.

show abstract

“…However, variations exist between the two protocols in the respective lifetimes of their TempIDs. While Tracetogether adopts the BlueTrace recommended 15 min lifetime of TempIDs, the CovidSafe resets its TempIDs every 120 min which could widen the replay attack windows [ 47 ]. Similar to the Tracetogether app, the CovidSafe app experienced an initial mass download of up to two million downloads within a day after release and above six million in a few weeks.…”

Section: Technology-based Contact Tracing Methods Against Covid-19mentioning

confidence: 99%

Non-Pharmaceutical Interventions against COVID-19 Pandemic: Review of Contact Tracing and Social Distancing Technologies, Protocols, Apps, Security and Open Research Directions

Alo¹,

Nkwo²,

Nweke

et al. 2021

Sensors

View full text Add to dashboard Cite

The COVID-19 Pandemic has punched a devastating blow on the majority of the world’s population. Millions of people have been infected while hundreds of thousands have died of the disease throwing many families into mourning and other psychological torments. It has also crippled the economy of many countries of the world leading to job losses, high inflation, and dwindling Gross Domestic Product (GDP). The duo of social distancing and contact tracing are the major technological-based non-pharmaceutical public health intervention strategies adopted for combating the dreaded disease. These technologies have been deployed by different countries around the world to achieve effective and efficient means of maintaining appropriate distance and tracking the transmission pattern of the diseases or identifying those at high risk of infecting others. This paper aims to synthesize the research efforts on contact tracing and social distancing to minimize the spread of COVID-19. The paper critically and comprehensively reviews contact tracing technologies, protocols, and mobile applications (apps) that were recently developed and deployed against the coronavirus disease. Furthermore, the paper discusses social distancing technologies, appropriate methods to maintain distances, regulations, isolation/quarantine, and interaction strategies. In addition, the paper highlights different security/privacy vulnerabilities identified in contact tracing and social distancing technologies and solutions against these vulnerabilities. We also x-rayed the strengths and weaknesses of the various technologies concerning their application in contact tracing and social distancing. Finally, the paper proposed insightful recommendations and open research directions in contact tracing and social distancing that could assist researchers, developers, and governments in implementing new technological methods to combat the menace of COVID-19.

show abstract

Scrutinising COVIDSafe: Frameworks for evaluating digital contact tracing technologies

Cited by 21 publications

References 6 publications

Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia

Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia

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

Non-Pharmaceutical Interventions against COVID-19 Pandemic: Review of Contact Tracing and Social Distancing Technologies, Protocols, Apps, Security and Open Research Directions

Contact Info

Product

Resources

About