Digital contact tracing contributes little to COVID-19 outbreak containment

Burdinski, Angelique; Brockmann, Dirk; Maier, Benjamin F.

doi:10.1101/2021.06.21.21259258

Cited by 4 publications

(1 citation statement)

References 54 publications

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“…On one hand, about 28 countries such as China, Switzerland, Spain, the United Kingdom, Australia, Singapore and Germany have implemented various measures using informa-tion technology (e.g., launching digital contact tracing apps) [10][11][12][13][14] . On the other hand, however, recent works have revealed that digital contact tracing contributes little to contain outbreaks, principally because of low participation rates and low engagement of participants 15,16 . As many controversial issues of digital contact tracing have been raised, it is urgent to review empirical evidence for the effectiveness of this measure against a pandemic spreading from different aspects [17][18][19] .…”

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confidence: 99%

Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

Shen

et al. 2021

Preprint

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Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected contacted individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

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confidence: 99%

Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

Shen

et al. 2021

Preprint

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Psychological factors shaping public responses to COVID-19 digital contact tracing technologies in Germany

Kozyreva

Lorenz-Spreen

Lewandowsky

et al. 2021

Sci Rep

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The COVID-19 pandemic has seen one of the first large-scale uses of digital contact tracing to track a chain of infection and contain the spread of a virus. The new technology has posed challenges both for governments aiming at high and effective uptake and for citizens weighing its benefits (e.g., protecting others’ health) against the potential risks (e.g., loss of data privacy). Our cross-sectional survey with repeated measures across four samples in Germany ($$N = 4357$$ N = 4357 ) focused on psychological factors contributing to the public adoption of digital contact tracing. We found that public acceptance of privacy-encroaching measures (e.g., granting the government emergency access to people’s medical records or location tracking data) decreased over the course of the pandemic. Intentions to use contact tracing apps—hypothetical ones or the Corona-Warn-App launched in Germany in June 2020—were high. Users and non-users of the Corona-Warn-App differed in their assessment of its risks and benefits, in their knowledge of the underlying technology, and in their reasons to download or not to download the app. Trust in the app’s perceived security and belief in its effectiveness emerged as psychological factors playing a key role in its adoption. We incorporate our findings into a behavioral framework for digital contact tracing and provide policy recommendations.

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Use of temporal contact graphs to understand the evolution of COVID-19 through contact tracing data

Shen

et al. 2022

Commun Phys

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Digital contact tracing has been recently advocated by China and many countries as part of digital prevention measures on COVID-19. Controversies have been raised about their effectiveness in practice as it remains open how they can be fully utilized to control COVID-19. In this article, we show that an abundance of information can be extracted from digital contact tracing for COVID-19 prevention and control. Specifically, we construct a temporal contact graph that quantifies the daily contacts between infectious and susceptible individuals by exploiting a large volume of location-related data contributed by 10,527,737 smartphone users in Wuhan, China. The temporal contact graph reveals five time-varying indicators can accurately capture actual contact trends at population level, demonstrating that travel restrictions (e.g., city lockdown) in Wuhan played an important role in containing COVID-19. We reveal a strong correlation between the contacts level and the epidemic size, and estimate several significant epidemiological parameters (e.g., serial interval). We also show that user participation rate exerts higher influence on situation evaluation than user upload rate does, indicating a sub-sampled dataset would be as good at prediction. At individual level, however, the temporal contact graph plays a limited role, since the behavior distinction between the infected and uninfected individuals are not substantial. The revealed results can tell the effectiveness of digital contact tracing against COVID-19, providing guidelines for governments to implement interventions using information technology.

show abstract

Digital contact tracing contributes little to COVID-19 outbreak containment

Cited by 4 publications

References 54 publications

Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

Temporal Contact Graph Reveals The Evolving Epidemic Situation of COVID-19

Psychological factors shaping public responses to COVID-19 digital contact tracing technologies in Germany

Use of temporal contact graphs to understand the evolution of COVID-19 through contact tracing data

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