Quantifying the effectiveness of digital contact tracing and isolation strategies for pandemic control, a new research based on empirical data
Contact tracing, both manual and potentially with digital apps, is considered a key ingredient in the control of infectious disease outbreaks. During the ongoing COVID-19 crisis, for example, it has been widely considered, discussed, and experimented in the strategies making it possible to alleviate the lockdown and to return to a quasi-normal functioning of society. However, the current leading modeling framework for evaluating contact tracing is highly stylized, lacking important features and heterogeneities present in real-world contact patterns that are relevant for epidemic dynamics.
A new paper out in Nature Communications considers a modeling framework extensively informed by real-world, high-resolution contact data to analyze the impact of digital (app-based) containment strategies for the COVID-19 pandemic. Digital proximity tracing on empirical contact networks for pandemic control is a joint work led by Fondazione Bruno Kessler (FBK), with Technical University of Denmark (DTU), Aix-Marseille Université, ISI Foundation and Università degli Studi di Torino. Among authors are several researchers, including ISI Ciro Cattuto, who contributed to the DP-3T protocol for privacy-preserving contact tracking, which inspired the Apple and Google exposure notification system used by many national tracking apps.
Analyzing data coming from experiences like SocioPatterns (a ten-year project led by ISI Foundation) and Copenhagen Network Study, scientists investigate how well contact tracing apps, coupled with the quarantine of identified contacts, can mitigate a spread in realistic scenarios such as a university campus, a workplace, or a high school. Results show that isolation strategies and digital contact tracing via app can help contain re-emerging outbreaks if certain conditions are met, particularly if propagation is complemented by other interventions such as the use of masks and physical distancing, if app adoption is high, and if the delay in contact isolation is minimal. The study also shows that second order contact tracking (contacts of contacts, more intrusive in terms of privacy) is not effective, and confirms that the exposure notification mechanism in use in most national apps, which is limited to contacts of the first order and minimizes the data collected, is adequate to achieve the benefits of digital contact tracing.
“Digital proximity tracing on empirical contact networks for pandemic control”, Giulia Cencetti, Gabriele Santin, Antonio Longa, Emanuele Pigani, Alain Barrat, Ciro Cattuto, Sune Lehmann, Marcel Salathé, Bruno Lepri. Nature Communications, 12th March 2021.