Beyond Center for Fundamental Concepts in Science, Arizona State University, Tempe, AZ, USA.
School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA.
J R Soc Interface. 2021 Feb;18(175):20200954. doi: 10.1098/rsif.2020.0954. Epub 2021 Feb 24.
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.
一种被广泛提倡的减缓 COVID-19 传播的方法是自动接触者追踪。由于个人移动设备可以收集接近数据，因此自然的建议是将其用于自动接触者追踪，这比手动实施有很大的优势。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在映射由于 SARS-CoV-2 传播而导致的大流行传播方面的有效性。我们强调了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口抽样不足的脆弱性，这导致无法充分确定与受感染个体的重要接触。至关重要的是，需要有相当一部分人口参与，我们为此推导出了一个最小阈值。我们的结论是，主要依靠自动接触者追踪而没有全民参与来控制 SARS-CoV-2 大流行的传播可能适得其反，并允许大流行不受控制地传播。同时实施各种缓解方法以及自动接触者追踪是遏制大流行的最佳解决方案的必要条件。
