The first GAEN-based COVID-19 contact tracing app in Norway identifies 80% of close contacts in "real life" scenarios.

The COVID-19 response in most countries depends on testing, isolation, contact tracing, and quarantine, which is labor- and time consuming. Therefore, several countries worldwide launched Bluetooth based apps as supplemental tools. We evaluated the new Norwegian GAEN (Google Apple Exposure Notification) based contact tracing app 'Smittestopp' under two relevant simulated scenarios, namely standing in a queue and riding public transport. We compared two configurations (C1: 58/63 dBm; C2: 58/68 dBm) with multiple weights (1.0-2.5) and time thresholds (10-15 min), by calculating notification rates among close contacts ([≤]2 meters, [≥]15 min) and other non-close contacts. In addition, we estimated the effect of using different operating systems and locations of phone (hand/pocket) using Chi2. C2 resulted in significantly higher notification rates than C1 (p-value 0.05 - 0.005). The optimal setting resulted in notifications among 80% of close contacts and 34% of other contacts, using C2 with weights of 2.0 for the low and 1.5 for the middle bucket with a 13-minutes time threshold. Among other contacts, the notification rate was 67% among those [≤]2 meters for <15 minutes compared to 19% among those >2 meters (p=0.004). Significantly (p-values 0.046 - 0.001) lower notification rates were observed when using the iOS operating systems or carrying the phone in the pocket instead of in the hand. This study highlights the importance of testing and optimizing the performance of contact tracing apps under 'real life' conditions to optimized configuration for identifying close contacts.