EAGER: Collaborative Research: Privacy-enhancing CrowdPCR for Early Epidemic Detection

EAGER：合作研究：用于早期流行病检测的增强隐私的 CrowdPCR

• 批准号: 1645121
• 负责人: Danfeng Yao
• 金额: $ 5万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1645121&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Privacy; enhancing

1645285/1645121Ugaz/DanfengThe PIs propose fundamental research aimed at establishing a new platform to leverage crowds (i.e., large numbers of non-technical savvy participants) as a resource to greatly expand capabilities for distributed detection of bacterial and viral pathogens. An inexpensive smartphone-based mobile laboratory platform enabling gold-standard nucleic acid-based analysis will be merged with a state-of-the-art crowd-sensing paradigm that permits large scale sensory data collection with low infrastructure support. These new capabilities will empower non-expert participants to perform rapid assays with smartphone connectivity, eliminating delays between sample collection and analysis so that test results can be delivered in minutes.This fundamental research addresses multiple thrusts in Public Participation in Engineering Research, focusing on Citizen Science and Crowdsourcing, including: (1) methodologies for distributed data collection, and, (2) new technologies for improved data collection. The proposed crowd-sensing approach will deliver a new platform to support a host of multidisciplinary citizen-science projects that require secure and privacy-preserving cyberinfrastructures. Secure crowd-sensing encourages participation, which in turn boosts the quality of data and discovery. The PIs envision that the efficiency and scalability of their methodology will help increase the real-world adoption of group signatures by developers, scientists and engineers in their crowd-sensing applications. The ultra-low cost of their bioanalytical instrumentation will also make it possible to deploy thousands at once to enable targeted diagnostics and monitoring. By making it feasible, for the first time, to deploy ensembles of thousands instruments for the same cost of a single dedicated laboratory analysis machine, their platform promises to bridge the gap between current-generation rapid diagnostic tests and the polymerase chain reaction gold standard. The United States clinical laboratory improvement amendments classify clinical diagnostic tests as either high, moderate, or waived complexity based upon the nature of the test performed. Polymerase chain reaction-based diagnostics are currently classified as high complexity due to prerequisite operational training and sophisticated instrumentation, thereby making them expensive and impractical for mass distribution in portable applications. The versatile platform proposed offers potential to enable polymerase chain reaction to be classified in the moderate or waived complexity categories, opening the door for a new generation of fast, accurate, and affordable diagnostic tools impacting a host of new scenarios where rapid field-deployable analysis is needed but not yet widely available (e.g., citizen science). Multi-disciplinary crowd-sensing and citizen-science projects require secure and privacy-preserving cyberinfrastructures. Secure crowd-sensing encourages participation, which in turn boosts the quality of data and discovery. The PIs envision that the efficiency and scalability of sublinear revocation with backward unlinkability helps increase the real-world adoption of group signatures by developers, scientists and engineers in their crowd-sensing applications.

1645285/1645121UGAZ/DANFENCTE PIS提出的基础研究旨在建立一个新的平台，以利用人群（即大量非技术精明的参与者）作为资源，以极大地扩大细菌和病毒病原体分布的发现的能力。基于智能手机的廉价移动实验室平台，可以将基于金标准的核酸分析与最先进的人群感应范式合并，该范式允许具有低基础架构支持的大规模感觉数据收集。这些新功能将使非专家参与者有能力通过智能手机连接进行快速测定，从而消除了样本收集和分析之间的延迟，因此可以在几分钟内提供测试结果。这项基本研究涉及公众参与工程研究的多重推力，重点是公民。科学和众包，包括：（1）分布式数据收集的方法论，以及（2）改进数据收集的新技术。拟议的人群感应方法将提供一个新的平台，以支持许多需要安全和隐私的网络基础设施的多学科公民科学项目。安全的人群感应鼓励参与，从而提高了数据和发现的质量。 PIS设想，其方法的效率和可扩展性将有助于提高开发人员，科学家和工程师在人群相关应用中对群体签名的采用。其生物分析仪器的超低成本也将使能够立即部署数千个以实现目标诊断和监测。通过使其首次以单个专用实验室分析机的相同成本部署数千个乐器的合奏，它们的平台有望弥合当前产生的快速诊断测试与聚合酶链链反应金标准之间的差距。美国的临床实验室改进修订将临床诊断测试分类为基于执行的测试性质的高，中度或放弃的复杂性。由于先决条件的操作培训和复杂的仪器，因此基于聚合酶链反应的诊断目前被归类为高复杂性，从而使它们对于便携式应用中的质量分布而变得昂贵且不切实际。多功能平台提出的潜力可以使聚合酶链反应分类为中等或放弃的复杂性类别，为新一代的快速，准确且负担得起的诊断工具打开了大门，影响了许多新场景，而快速现场可忽视分析的新场景需要但尚未广泛使用（例如，公民科学）。多学科的人群感应和公民科学项目需要安全和保护隐私的网络基础设施。安全的人群感应鼓励参与，从而提高了数据和发现的质量。 PIS设想，具有向后的不链接性的sublinear撤销的效率和可扩展性有助于提高开发人员，科学家和工程师在人群相关应用中对群体签名的现实采用。