论文标题

实现自动化曝光通知(AEN)技术的承诺,以控制Covid-19的传播:智能手机应用程序部署,使用和迭代评估的建议

Realizing the Promise of Automated Exposure Notification (AEN) Technology to Control the Spread of COVID-19: Recommendations for Smartphone App Deployment, Use, and Iterative Assessment

论文作者

Alekseyev, Jesslyn, Dixon, Erica, Woltz, Vilhelm L Andersen, Weitzner, Danny

论文摘要

通过使用现代的加密技术,保护自动曝光通知(AEN)技术可以通过在孵化期内自动记录人之间的接触,同时保持个人数据隐私,从而减轻疾病传播的承诺。如今,全世界和世界其他国家的公共卫生部门正在快速部署AEN系统。尽管许多组织在部署应用程序之前进行了研究,但世界各地的经验表明,接触追踪应用程序的安装和使用相对较低。该白皮书旨在为正在考虑部署AEN系统的州提供可用信息,并指导已经部署的州正在进行的改进。我们概述了与使用AEN系统有关的人为因素的考虑因素,其最终目标是控制Covid-19的传播,包括Gaen Consortium暴露通知(EN)Express工具。我们还将为各州和其他人设计和部署AEN系统提供实用的设计和实施指南,以及一组评估联系人跟踪应用程序的部署和针对关注的领域以提高初始部署期间使用效率的建议。作为一个案例研究,我们考虑宾夕法尼亚州(PA)部署的商业应用程序以及持续推动在此采用用户采用的努力。

By using modern cryptographic techniques, privacy-preserving Automated Exposure Notification (AEN) technologies offer the promise of mitigating disease spread by automatically recording contacts between people over the incubation period while maintaining individual data privacy. Today, public health departments in States and other countries around the world are deploying AEN systems at a rapid pace. Though many organizations conducted research prior to deploying apps, experience around the world shows that contact-tracing apps are installed and used at relatively low levels. This whitepaper is intended to provide usable information for States who are considering the deployment of an AEN system, as well as to guide ongoing improvements for States that have already deployed. We outline the human factors considerations related to employing AEN systems with the ultimate goal of controlling the spread of COVID-19, including the GAEN consortium Exposure Notifications (EN) Express tool. We will also provide a practical design and implementation guide for States and others designing and deploying AEN systems, as well as a set of recommendations for assessing deployment of contact tracing apps and targeting areas of concern to improve efficacy of use during and after initial deployment. As a case study, we consider the commercial app deployed by the state of Pennsylvania (PA) and the ongoing efforts to drive user adoption there.

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