Suchergebnisse

While Digital contact tracing (DCT) has been argued to be a valuable complement to manual tracing in the containment of COVID-19, no empirical evidence of its effectiveness is available to date. Here, we report the results of a 4-week population-based controlled experiment that took place in La Gomera (Canary Islands, Spain) between June and July 2020, where we assessed the epidemiological impact of the Spanish DCT app Radar Covid. After a substantial communication campaign, we estimate that at least 33% of the population adopted the technology and further showed relatively high adherence and compliance as well as a quick turnaround time. The app detects about 6.3 close-contacts per primary simulated infection, a significant percentage being contacts with strangers, although the spontaneous follow-up rate of these notified cases is low. Overall, these results provide experimental evidence of the potential usefulness of DCT during an epidemic outbreak in a real population. ; This work was funded by the Secretary of State of Digitalisation and Artificial Intelligence, Ministry of Economic Affairs and Digital Transformation, Government of Spain. We thank Government of Spain, Gobierno de Canarias, INDRA, CCN, Fundación ONCE and the EU e-health Network for continuous support. We also thank Elisa Molino, Isabel Zanforlin, Alberto Ricci (Apple) and María Álvarez, Julián Toledo, Marcel Pinto (Google), Jorge García Vidal, Fernando Cucchietti, Josep Martorell and Mateo Valero (BSC). This work was made possible thanks to the incredible collaboration and engagement of the citizens of San Sebastián de la Gomera, Canary Islands (Spain). We also thank the DP3T community for helpful discussions. AA acknowledges financial support from Spanish MINECO (grant PGC2018-094754-B-C21), Generalitat de Catalunya (grant No. 2017SGR-896), and the James S. McDonnell Foundation (grant #220020325). LL acknowledges funding by EPSRC EC Fellowship EP/P01660X/1 and a QMUL COVID-19 Rapid Response Grant. JSM acknowledges funding by a Starting Grant from the European Research Council (grant #759903). ; Peer reviewed