论文标题
自动接触跟踪：Covid-19时期的大数字游戏
Automated Contact Tracing: a game of big numbers in the time of COVID-19
论文作者
论文摘要
降低Covid-19的扩散的最广泛倡导的解决方案之一是自动接触跟踪。由于可以通过个人移动设备收集接近性数据，因此自然建议是将其用于自动接触跟踪，从而为手动实施提供了重大收益。在这项工作中，我们研究了自愿和自动接触跟踪的特征及其由于SARS-COV-2的扩散而绘制大流行的有效性。我们强调自动接触跟踪所需的基础架构和社会结构。我们显示了该策略不足以对人口采样的脆弱性，这导致无法充分确定与受感染者的显着接触。至关重要的重要性将是我们得出最低阈值的大部分人口的参与。我们得出的结论是，在很大程度上依靠自动接触跟踪而没有人口范围的参与来遏制SARS-COV-2大流行的传播，这可能会适得其反，并使大流行不受任何检查。对于达到最佳解决方案以遏制大流行是必要的，同时实施了各种缓解方法以及自动接触跟踪。
One of the more widely advocated solutions for slowing down the spread of COVID-19 has been automated contact tracing. Since proximity data can be collected by personal mobile devices, the natural proposal has been to use this for automated contact tracing providing a major gain over a manual implementation. In this work, we study the characteristics of voluntary and automated contact tracing and its effectiveness for mapping the spread of a pandemic due to the spread of SARS-CoV-2. We highlight the infrastructure and social structures required for automated contact tracing to work. We display the vulnerabilities of the strategy to inadequate sampling of the population, which results in the inability to sufficiently determine significant contact with infected individuals. Of crucial importance will be the participation of a significant fraction of the population for which we derive a minimum threshold. We conclude that relying largely on automated contact tracing without population-wide participation to contain the spread of the SARS-CoV-2 pandemic can be counterproductive and allow the pandemic to spread unchecked. The simultaneous implementation of various mitigation methods along with automated contact tracing is necessary for reaching an optimal solution to contain the pandemic.
