Department of Otolaryngology - Head and Neck Surgery, University of California, Irvine, Irvine, CA, United States.
Department of Biomedical Engineering, University of California, Irvine, Irvine, CA, United States.
JMIR Mhealth Uhealth. 2020 Apr 7;8(4):e18936. doi: 10.2196/18936.
The novel coronavirus disease 2019 (COVID-19) pandemic is an urgent public health crisis, with epidemiologic models predicting severe consequences, including high death rates, if the virus is permitted to run its course without any intervention or response. Contact tracing using smartphone technology is a powerful tool that may be employed to limit disease transmission during an epidemic or pandemic; yet, contact tracing apps present significant privacy concerns regarding the collection of personal data such as location.
The aim of this study is to develop an effective contact tracing smartphone app that respects user privacy by not collecting location information or other personal data.
We propose the use of an anonymized graph of interpersonal interactions to conduct a novel form of contact tracing and have developed a proof-of-concept smartphone app that implements this approach. Additionally, we developed a computer simulation model that demonstrates the impact of our proposal on epidemic or pandemic outbreak trajectories across multiple rates of adoption.
Our proof-of-concept smartphone app allows users to create "checkpoints" for contact tracing, check their risk level based on their past interactions, and anonymously self-report a positive status to their peer network. Our simulation results suggest that higher adoption rates of such an app may result in a better controlled epidemic or pandemic outbreak.
Our proposed smartphone-based contact tracing method presents a novel solution that preserves privacy while demonstrating the potential to suppress an epidemic or pandemic outbreak. This app could potentially be applied to the current COVID-19 pandemic as well as other epidemics or pandemics in the future to achieve a middle ground between drastic isolation measures and unmitigated disease spread.
新型冠状病毒病 2019（COVID-19）大流行是一场紧迫的公共卫生危机，如果不采取任何干预或应对措施，任由病毒传播，预计会产生严重后果，包括高死亡率。使用智能手机技术进行接触者追踪是一种强大的工具，可以在疫情或大流行期间限制疾病传播；然而，接触者追踪应用程序在收集个人数据（如位置）方面存在重大隐私问题。
本研究旨在开发一种有效的接触者追踪智能手机应用程序，通过不收集位置信息或其他个人数据来尊重用户隐私。
我们建议使用人际互动的匿名图来进行一种新形式的接触者追踪，并开发了一个概念验证的智能手机应用程序来实现这种方法。此外，我们开发了一个计算机模拟模型，演示了我们的方案对多种采用率的传染病或大流行爆发轨迹的影响。
我们的概念验证智能手机应用程序允许用户创建接触者追踪的“检查站”，根据他们过去的互动检查他们的风险水平，并匿名向他们的同行网络自我报告阳性状态。我们的模拟结果表明，更高的采用率可能会导致传染病或大流行的爆发得到更好的控制。
我们提出的基于智能手机的接触者追踪方法提供了一种既保护隐私又具有抑制传染病或大流行爆发潜力的新解决方案。该应用程序可能会被应用于当前的 COVID-19 大流行以及未来的其他传染病或大流行，以在严格的隔离措施和不受控制的疾病传播之间取得平衡。
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