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Digital contact tracing and notification were initially hailed as promising strategies to combat SARS-CoV-2; however, in most jurisdictions, they did not live up to their promise. To avert a given transmission event, both parties must have adopted the technology, it must detect the contact, the primary case must be promptly diagnosed, notifications must be triggered, and the secondary case must change their behavior to avoid the focal tertiary transmission event. If we approximate these as independent events, achieving a 26% reduction in the effective reproduction number Rt would require an 80% success rate at each of these 6 points of failure. Here, we review the 6 failure rates experienced by a variety of digital contact tracing and contact notification schemes, including Singapore's TraceTogether, India's Aarogya Setu, and leading implementations of the Google Apple Exposure Notification system. This leads to a number of recommendations, for example, that the narrative be framed in terms of user autonomy rather than user privacy, and that tracing/notification apps be multifunctional and integrated with testing, manual contact tracing, and the gathering of critical scientific data.

Samenvatting De CoronaMelder-app is een van de middelen die ingezet worden om het coronavirus te bestrijden. Met de app worden twee doelen nagestreefd: 1. CoronaMelder wordt gebruikt als aanvulling op het reguliere bron- en contactonderzoek (BCO) om sneller en meer nauwe contacten te bereiken na een positieve testuitslag. 2. CoronaMelder moet de verspreiding van het coronavirus tegengaan door advies (de zogenaamde handelingsperspectieven) te geven na een melding aan haar gebruikers. Denk aan: ‘laat je testen’ of ‘blijf thuis’. Na de introductie van de app is een doorlopende evaluatie gestart om na te gaan of CoronaMelder deze twee doelen in de praktijk bereikt en in hoeverre er daarbij al dan niet negatieve onbedoelde effecten optreden. Deze doorlopende evaluatie bestaat uit verschillende individuele onderzoeken. Bij de doorlopende evaluatie wordt overigens niet alleen vastgesteld in hoeverre de doelen gehaald worden. De resultaten van de doorlopende evaluatie zijn ook gebruikt om waar nodig aanpassingen voor te stellen in de app, de bijbehorende handelingsperspectieven, de communicatie en in het beleid. Negen maanden na invoering van CoronaMelder is ook een aantal epidemiologische impactstudies gereed. Daarmee zijn we nu in staat om alle bevindingen bij elkaar te brengen uit de onderzoeken die tot dusver deel hebben uitgemaakt van de doorlopende evaluatie naar CoronaMelder.

Contact tracing apps (CTAs) have been introduced as a means to identify and isolate possible cases infected with COVID-19. Since the adoption rate determines the effectiveness of CTAs, it is important to examine what factors contribute to a higher CTA uptake. This study aimed to use an integrative approach to explain early CTA adoption, whereby three perspectives are distinguished: technology-related (derived from the Unified Theory of Acceptance and Use of Technology [UTAUT]), health-related (derived from the Health Belief Model [HBM]), and context-related. A survey was administered among a representative sample of the Dutch population (N = 1865). A hierarchical logistic regression analysis was performed in which the models were compared. Results showed that an integrative model including all three perspectives (i.e., UTAUT, HBM, and context-related variables) resulted in better model fit than any of the other models. All UTAUT variables were associated with CTA adoption in the expected directions. Regarding the HBM, self-efficacy, perceived barriers and perceived benefits were associated with CTA adoption in the expected directions. Several context-related variables, such as fear, were associated with CTA adoption. Our findings demonstrate that extending the UTAUT with preventive health-behavioral factors and contextual factors contribute to better understanding of CTA adoption.

The success of new technologies such as contact tracing mobile applications depends on large-scale end-user adoption. However, the implementation may encounter resistance, since the uncertainty surrounding novel technology may raise anxiety, and persuasion efforts to promote use can evoke reactance. Thereby, anxiety and reactance are two forms of resistance to new technology. Little is known about the role of resistance over the course of the innovation implementation process, in a social environment where technology functionality depends on adoption by others. Therefore, this four-wave longitudinal study followed adoption of the Dutch COVID-19 contact tracing app during four months (N = 1120), and explored the time dynamics and interplay of reactance to freedom threat, anxiety, and perceived social norms on app use. Mixed-effect analyses showed that anxiety and, subtly, reactance decreased with time; initial freedom threat predicted later reactance. App use related negatively to reactance and anxiety; and positively to positive social norms. Over time, the norm effect was mediated by lower reactance and anxiety. The results imply that resistance is pervasive, suggest that self perceived app use norms may be key to overcoming resistance to new applications, and demonstrate that theories predicting innovation or technology acceptance benefit from studying predictors over time.

Het doel van het coronatoegangsbewijs als voorwaarde voor deelname aan specifieke activiteiten is om de samenleving op verantwoorde wijze open te houden in een periode dat de vaccinatiegraad nog ontoereikend is. De gedachte is dat door het coronatoegangsbewijs het risico op besmetting zodanig verlaagd kan worden, dat beperkende maatregelen kunnen worden versoepeld of losgelaten en sneller toegang kan worden gegeven tot bepaalde voorzieningen of activiteiten. Hiertoe is een digitale applicatie voor het coronatoegangsbewijs ontwikkeld: CoronaCheck.