论文标题
社交距离2.0具有隐私权联系人跟踪，以避免第二波Covid-19
Social Distancing 2.0 with Privacy-Preserving Contact Tracing to Avoid a Second Wave of COVID-19
论文作者
论文摘要
如何在重新开放经济后避免第二波Covid-19是一个紧迫的问题。 SARS-COV-2的极高基本生殖数量$ R_0 $（5.7至6.4）进一步使挑战更加复杂。在这里，我们评估社会距离2.0的效果，即邻近警报（维持个人间距离）以及保护隐私的联系跟踪。为了解决双重任务，我们开发了一个开源移动应用程序。该应用程序使用基于蓝牙的，分散的接触跟踪平台，在该平台上，匿名用户ID无法由政府或第三方链接。建模结果表明，具有保护隐私的接触跟踪的社会距离2.0的50％采用率足以将$ R_0 $降低至小于1的$ R_0 $，并防止Covid-19的流行病的复兴。
How to avoid a second wave of COVID-19 after reopening the economy is a pressing question. The extremely high basic reproductive number $R_0$ (5.7 to 6.4, shown in new studies) of SARS-CoV-2 further complicates the challenge. Here we assess effects of Social distancing 2.0, i.e. proximity alert (to maintain inter-personal distance) plus privacy-preserving contact tracing. To solve the dual task, we developed an open source mobile app. The app uses a Bluetooth-based, decentralized contact tracing platform over which the anonymous user ID cannot be linked by the government or a third party. Modelling results show that a 50\% adoption rate of Social distancing 2.0, with privacy-preserving contact tracing, would suffice to decrease the $R_0$ to less than 1 and prevent the resurgence of COVID-19 epidemic.
