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.

自动接触者追踪是最广泛提倡的减缓 COVID-19 传播的解决方案之一。由于接近数据可以通过个人移动设备收集，因此自然的建议是使用它来进行自动接触者追踪，这比手动实施有很大的好处。在这项工作中，我们研究了自愿和自动接触者追踪的特征及其对绘制由于 SARS-CoV-2 传播而导致的大流行病传播的有效性。我们重点介绍自动接触者追踪工作所需的基础设施和社会结构。我们展示了该策略对人群抽样不足的弱点，这导致无法充分确定与感染者的重大接触。至关重要的是很大一部分人口的参与，我们为此设定了最低门槛。我们的结论是，在没有全民参与的情况下，主要依靠自动接触者追踪来遏制 SARS-CoV-2 大流行的传播可能会适得其反，并使大流行不受控制地传播。为了找到遏制疫情的最佳解决方案，必须同时实施各种缓解方法以及自动接触者追踪。