Automated Contact Tracing System for Rapid High-Accuracy Assessment to Management Dementia Patients and Staff Exposed to Infectious Diseases in Long Term Care Facilities

自动接触者追踪系统，用于对长期护理机构中暴露于传染病的痴呆症患者和工作人员进行快速高精度评估

• 批准号: 10671765
• 负责人: Suneel Ismail Sheikh
• 金额: $ 129.15万
• 依托单位: ASTER LABS, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10671765
• 关键词: 2019-nCoV; Address; Administrator; Affect; Age; Algorithms; Alzheimer' s Disease; Alzheimer' s disease related dementia; American; Back; Behavior; COVID-19; COVID-19 pandemic; Car Phone; Caregivers; Caring; Cellular Phone; Communicable Diseases; Communities; Complex; Computer software; Contact Tracing; Data; Data Storage and Retrieval; Dementia; Devices; Diagnosis; Disease; Disease Management; Disease Outbreaks; Elderly; Electronics; Engineering; Environment; Epidemiology; Evaluation; Event; Exhibits; Exposure to; Florida; Focus Groups; Health; Health care facility; Human; Human Resources; Individual; Infection Control; Infrastructure; Intelligence; Interview; Investments; Laboratories; Lead; Life; Light; Location; Logistics; Long-Term Care; Manuals; Measures; Methods; Modification; Motion; Movement; Nursing Homes; Outcome; Patients; Performance; Persons; Phase; Population; Predisposition; Prevention; Process; Production; Recording of previous events; Reporting; Research; Research Personnel; Research Training; Resources; Retrieval; Risk; Risk Assessment; Route; Safety; Secure; Series; Shoes; Small Business Innovation Research Grant; Specific qualifier value; Symptoms; System; Technology; Testing; Time; Tracer; Training; United States; Universities; Virus; Work; aging in place; base; community living; community setting; comparative; contagion; cost; data access; data communication; data management; design; distrust; efficacy evaluation; efficacy study; experience; experimental study; functional independence; health care settings; healthcare-associated infections; high risk; human study; memory care; operation; patient home care; phase 1 testing; privacy protection; programs; prototype; response; sensor; success; system architecture; tool; vulnerable community; wearable device; web app; web platform

Project Abstract In this Fast-Track SBIR project, ASTER Labs will address an urgent, immediate, need for accessible and accurate contact tracing to aid management of infectious disease outbreaks in long-term care facilities of patients with Alzheimer’s disease and related dementias. An estimated 5.8 million Americans in 2020 live with Alzheimer’s dementia and nearly half of nursing home and other long-term care residents have been diagnosed with a form of dementia. Challenges in infectious disease management in these care settings are increased by frequent interactions between patients, caregivers, staff, and visitors, as well as higher risk from contagion due to age and underlying health conditions. The COVID-19 pandemic has only exacerbated the issue due to the susceptibility of the elderly to the virus. Contact tracing to identify, test, and isolate those who may have been exposed to an infected person has traditionally been a manual, labor-intensive process. Many care facilities lack the financial, human, and logistical resources to track sufficient detail to retrace movements. For dementia patients in particular, limited recall of recent events and interactions, inability to respond to tracing questions, and potential distrust of tracers risk inaccurate data. Investment in human resources to perform contact tracing is costly, and ad hoc tracing can limit effective outcomes. Existing methods to automate contact tracing have largely been smartphone software applications, widely criticized for lack of privacy protection, and in long-term care settings, guarantees on mobile phone use are limited. The few available solutions for care facilities rely on non-discreet wearable devices that, due to unfamiliarity, may be unacceptable to dementia patients, and often require large infrastructure additions with limitations on range. Therefore, there exists a significant unmet need to support care facilities by providing an unobtrusive, on- demand, accurate, and automated contact tracing solution that works both indoors and outdoors with little to no infrastructure requirements, and that addresses the special needs of dementia patients. ASTER Labs’ proposed Activtrace system leverages intelligent processing of WiFi, GPS, cellular, and inertial sensor data from a small hardware suite concealed in a shoe insole, unnoticeable to the wearer, that achieves high- precision location and duration of close-contact encounters in complex indoor and outdoor environments. In Phase I, the prototype system will be assembled, and feasibility will be demonstrated by determining the positional and temporal accuracy of the device in timed motion experiments, and through a focus group study with contact tracers and caregivers in senior care settings. Phase I testing will provide the success criteria for the start of the Phase II program. In Phase II, the pre-production insoles and comprehensive software application will be assembled, and the integrated system evaluated in a study with research actors wearing the insoles, along with confederate targets. Comparisons of results done manually by trained contact tracers and the automated Activtrace solution in multiple planned scenarios will establish the system’s efficacy.

项目摘要 在这个快速轨道 SBIR 项目中，ASTER Labs 将解决可访问且即时的紧急需求 准确的接触者追踪有助于管理长期护理机构中的传染病爆发 预计到 2020 年，将有 580 万美国人患有阿尔茨海默病和相关痴呆症。 阿尔茨海默氏症和近一半的疗养院和其他长期护理居民都患有阿尔茨海默氏症 被诊断患有某种形式的痴呆症的患者在这些护理机构中的传染病管理面临着挑战。 由于患者、护理人员、工作人员和访客之间的频繁互动以及来自患者的更高风险而增加 由于年龄和潜在的健康状况而导致的传染只会使情况更加恶化。 由于老年人对病毒易感性，因此需要进行接触者追踪，以识别、测试和隔离那些人。 传统上，与感染者接触可能是一个手动、劳动密集型的过程。 护理机构缺乏财力、人力和后勤资源来追踪足够的细节来追踪活动。 特别是对于痴呆症患者来说，对最近发生的事件和互动的回忆有限，无法对 追踪问题以及对追踪者的潜在不信任可能会导致数据不准确。 进行接触者追踪的成本很高，而且临时追踪可能会限制现有方法的有效结果。 自动接触者追踪主要是智能手机软件应用程序，因缺乏 隐私保护，并且在长期护理环境中，对手机使用的保证是有限的。 护理机构的可用解决方案依赖于非谨慎的可穿戴设备，由于不熟悉，这些设备可能会 这对痴呆症患者来说是不可接受的，并且通常需要增加大量基础设施，且范围有限。 因此，通过提供不引人注目的、现场的服务来支持护理机构，存在着巨大的未满足的需求。 按需、准确、自动化的接触者追踪解决方案，可在室内和室外使用，几乎不需要任何操作 基础设施要求，并满足 ASTER 实验室的特殊需求。 拟议的 Activtrace 系统利用 WiFi、GPS、蜂窝和惯性传感器数据的智能处理 来自隐藏在鞋垫中的小型硬件套件，穿着者不会注意到，从而实现了高 复杂室内外环境下近距离接触的精确定位和持续时间。 第一阶段，将组装原型系统，并通过确定 通过焦点小组研究，定时运动实验中设备的位置和时间精度 与高级护理机构中的接触者追踪者和护理人员一起进行第一阶段测试将提供成功标准。 第二阶段计划开始 在第二阶段，预生产鞋垫和综合软件。 应用程序将被组装，并在研究参与者佩戴的研究中评估集成系统 鞋垫，以及由受过训练的接触追踪者手动完成的结果的比较。 多个计划场景中的自动化 Activtrace 解决方案将确定系统的功效。