Profiling adopters (and non-adopters) of a contact tracing mobile application: Insights from Australia

Predicting the use of a COVID-19 contact tracing application: A study across two points of measurements

Contact tracing mobile applications (apps) were important in combating the COVID-19 pandemic. Most previous studies predicting contact tracing app use were cross-sectional and not theory-based. This study aimed at contributing to a better understanding of app use intentions and app use by applying an extended version of the protection motivation theory across two measurement points while accounting for the development of the pandemic. A total of N = 1525 participants from Switzerland (Mage = 53.70, SD = 18.73; 47% female; n = 270 completed both assessments) reported on risk perceptions, response efficacy, self-efficacy, social norms, trust in government, trust in the healthcare system, active search of COVID-19-related information, intentions for and actual (self-reported) app use. Analyses included country-specific incidences and death toll. Increases in response-efficacy, self-efficacy, trust in government, and the active search of COVID-19-related information predicted increased app-use intentions. Increases in self-efficacy, intentions, and the active search of COVID-19-related information predicted increased self-reported app use. Risk perceptions, incidence, and death toll were unrelated to both outcomes. Across an aggravation of the pandemic situation, intentions for and app use were primarily related to response-efficacy, self-efficacy, trust in government, and the active search of COVID-19-related information.

Systematic scoping review of the implementation, adoption, use, and effectiveness of digital contact tracing interventions for COVID-19 in the Western Pacific Region

A systematic scoping review of digital contact tracing (DCT) interventions for COVID-19 was conducted to describe the implementation, adoption, use and effectiveness of DCT interventions implemented as part of the COVID-19 response in the Western Pacific Region (WPR). A systematic search identified 341 studies and 128 grey literature sources, of which 18 studies and 41 grey literature sources were included. 17 (46%) WPR countries and areas implemented DCT interventions. Adoption ranged from 14.6% to 92.7% in different adult populations and epidemiological contexts. Trust in authorities, and privacy concerns and beliefs, were the most frequent determinants of adoption and use. Only two studies analysed DCT effectiveness, which showed limited to no effectiveness of DCT interventions in low transmission settings. Overall, there is limited evidence available to evaluate the contribution of DCT to mitigating COVID-19 in the WPR. Preparedness for future health emergencies should include developing robust frameworks for DCT effectiveness evaluations.

A fuzzy-set qualitative comparative analysis exploration of multiple paths to users' continuous use behavior of diabetes self-management apps

BACKGROUND

Despite the obvious potential benefits of diabetes self-management apps, users' continuous use of diabetes self-management apps is still not widespread. Influential factors coexisted in information ecologies are likely to have a synthetic effect on users' continuous use behavior. However, it is less clear how factors in information ecologies combine to influence users' continuous use behavior.

OBJECTIVE

The objectives of this study are to explore combinations of factors (perceived severity, information quality, service quality, system quality, and social influence) in information ecologies that lead to users' continuous use behavior of diabetes self-management apps and which combination is the most important.

METHODS

Purpose sampling was used to recruit diabetes self-management app users from July 1, 2021 to January 31, 2022. Fuzzy-set qualitative comparative analysis (fsQCA) was then employed by conducting necessity and sufficiency analysis.

RESULTS

In total 280 diabetes self-management app users participated. The necessity analysis indicated that no single factor was necessary to cause users' continuous use behavior, and the sufficiency analysis identified five different combinations of factors that lead to users' continuous use behavior. Of these five, the combination of high information quality, high service quality, and high social influence was found to be the most important path.

CONCLUSIONS

Users' continuous use behavior of diabetes self-management apps results from the synergistic effects of factors in information ecologies. The five paths that directly contribute to users' continuous use, as well as the four user types preliminarily identified in this study may provide a reference for healthcare providers and app developers.

Digital contact tracing during the COVID-19 pandemic in France: Associated factors and reasons for non-use

OBJECTIVES

To estimate the proportion of users of the TousAntiCovid app(lication) and identify factors associated with its non-use for contact tracing.

METHODS

We conducted an online survey of a quota sample of French adults between 8 and 18 January 2021. Three categories of TousAntiCovid use were considered: contact tracing, other or temporary usage, and no use. A weighted multiple logistic regression was performed to analyze the factors associated with these different uses.

RESULTS

Among the 1000 respondents, 63.3% declared they had never downloaded the TousAntiCovid app, 23.5% used it for contact tracing. The remaining 13.2% did not enable contact tracing, mainly because of excessive battery consumption and fear of misuse of personal data. Trust in political representatives, financial deprivation and other factors were associated with never downloading the app.

CONCLUSION

This study confirms the previously suggested links between trust in political representatives, financial deprivation and the use of contact tracing apps in France.

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

As part of their public health policies, most countries have launched mobile tracing applications (apps) to reduce the spread of the COVID-19 virus and reassure their citizens. To the best of our knowledge, no study has explored the importance of 'well-being' and 'trust in the future' in the context of digital contact-tracing apps. This is an important gap, especially given the importance of citizens' acceptance of a mobile tracing app and its role in reassuring citizens. Therefore, we study the French government's tracing app-StopCovid-as experienced by a sample of 832 participants from France. The results establish strong links between perceived value and trust in government, well-being, and trust in the future, which are considered the key features of the reassurance effect in a pandemic context. In addition, a multigroup analysis (MGA) allows us to compare the effect of several moderators on the overall model, such as the users versus nonusers of tracking apps or infected versus noninfected with COVID-19. The study provides practical implications by highlighting how governments should deploy mobile tracing apps to contribute to public health and reassure their citizens during the pandemic.

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

BACKGROUND

Digital proximity tracing apps 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 app for COVID-19.

METHODS

In this prospective study, done in New South Wales (NSW), Australia, we included all individuals in the state who were older than 12 years with confirmed, locally acquired SARS-CoV-2 infection between May 4 and Nov 4, 2020. We used data from the NSW Notifiable Conditions Information Management System, the national COVIDSafe database, and information from case interviews, including information on app usage, the number of app-suggested contacts, and the number of app-suggested contacts determined by public health staff to be actual close contacts. 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 done to assess the app's perceived usefulness.

FINDINGS

There were 619 confirmed COVID-19 cases with more than 25 300 close contacts identified by conventional contact tracing during the study period. COVIDSafe was used by 137 (22%) cases and detected 205 contacts, 79 (39%) of whom met the close contact definition. Its positive predictive value was therefore 39%. 35 (15%) of the 236 close contacts who could have been expected to have been using the app during the study period were identified by the app, making its estimated sensitivity 15%. 79 (0·3%) of the estimated 25 300 contacts in NSW were app-suggested and met the close contact definition. The app detected 17 (<0·1%) additional close contacts who were not identified by conventional contact tracing. COVIDSafe generated a substantial additional perceived workload for public health staff and was not considered useful.

INTERPRETATION

The low uptake of the app among cases probably led to a reduced sensitivity estimate in our study, given that only contacts who were using the app could be detected. COVIDSafe 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. We provide an empirical evaluation of this digital contact tracing app that questions the potential benefits of digital contact tracing apps to the public health response to COVID-19. Effectiveness evaluations should be integrated into future implementations of proximity contact tracing systems to justify their investment.

FUNDING

New South Wales Ministry of Health (Australia); National Health and Medical Research Council (Australia).

Digital contact-tracing in France: uptake by COVID-19 risk factor and by exposure risk

BACKGROUND

Few studies have investigated the influence of COVID-19 conspiracy theories on digital contact-tracing adoption and the differentiated uptake of digital contact-tracing by COVID-19 risk factor and by exposure risk.

METHODS

Using a cross-sectional survey conducted in France in November 2020 (N = 1042), we investigate the factors associated with the use of the French 'TousAntiCovid' contact-tracing application. Our independent variables of interest include COVID-19 and 'TousAntiCovid' perceptions, trust in the government, time and risk preferences and the level of adherence to COVID-19 conspiracy theories. We conduct regression analyses by COVID-19 risk factor and exposure groups.

RESULTS

Among the full sample, a negative association is found between the propensity to believe in COVID-19 conspiracy theories and the use of 'TousAntiCovid'. French respondents at risk of severe COVID-19 form are more likely to use 'TousAntiCovid'. No difference in uptake is found by exposure group. Group analyses indicate that the factors associated with the uptake of digital contact-tracing differ by COVID-19 risk factor and exposure risk.

CONCLUSION

Governmental communication to fight COVID-19 misinformation and to stress out the utility and data safety of 'TousAntiCovid' should be reinforced. Targeted communication campaigns should be conducted among low adoption groups and key groups in COVID-19 transmission.

Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature

BACKGROUND

Digital contact tracing apps have the potential to augment contact tracing systems and disrupt COVID-19 transmission by rapidly identifying secondary cases prior to the onset of infectiousness and linking them into a system of quarantine, testing, and health care worker case management. The international experience of digital contact tracing apps during the COVID-19 pandemic demonstrates how challenging their design and deployment are.

OBJECTIVE

This study aims to derive and summarize best practice guidance for the design of the ideal digital contact tracing app.

METHODS

A collaborative cross-disciplinary approach was used to derive best practice guidance for designing the ideal digital contact tracing app. A search of the indexed and gray literature was conducted to identify articles describing or evaluating digital contact tracing apps. MEDLINE was searched using a combination of free-text terms and Medical Subject Headings search terms. Gray literature sources searched were the World Health Organization Institutional Repository for Information Sharing, the European Centre for Disease Prevention and Control publications library, and Google, including the websites of many health protection authorities. Articles that were acceptable for inclusion in this evidence synthesis were peer-reviewed publications, cohort studies, randomized trials, modeling studies, technical reports, white papers, and media reports related to digital contact tracing.

RESULTS

Ethical, user experience, privacy and data protection, technical, clinical and societal, and evaluation considerations were identified from the literature. The ideal digital contact tracing app should be voluntary and should be equitably available and accessible. User engagement could be enhanced by small financial incentives, enabling users to tailor aspects of the app to their particular needs and integrating digital contact tracing apps into the wider public health information campaign. Adherence to the principles of good data protection and privacy by design is important to convince target populations to download and use digital contact tracing apps. Bluetooth Low Energy is recommended for a digital contact tracing app's contact event detection, but combining it with ultrasound technology may improve a digital contact tracing app's accuracy. A decentralized privacy-preserving protocol should be followed to enable digital contact tracing app users to exchange and record temporary contact numbers during contact events. The ideal digital contact tracing app should define and risk-stratify contact events according to proximity, duration of contact, and the infectiousness of the case at the time of contact. Evaluating digital contact tracing apps requires data to quantify app downloads, use among COVID-19 cases, successful contact alert generation, contact alert receivers, contact alert receivers that adhere to quarantine and testing recommendations, and the number of contact alert receivers who subsequently are tested positive for COVID-19. The outcomes of digital contact tracing apps' evaluations should be openly reported to allow for the wider public to review the evaluation of the app.

CONCLUSIONS

In conclusion, key considerations and best practice guidance for the design of the ideal digital contact tracing app were derived from the literature.