Solving the problem of detecting asymptomatic carriers who can transmit infection is key to protecting vulnerable residents of nursing homes and assisted living facilities, to protecting frontline workers who care for them, and to facilitating return to work (including return of nurses and medical assistants). The wearable biometric technology, if widely disseminated among vulnerable populations and the community-at-large, will help avoid the ravages of seasonal flu and other contagious illnesses, and the society will be better prepared for future waves of COVID-19 or other pandemics. Even if a vaccine is developed, due to immune senescence and immunocompromise, elderly people and those with chronic medical conditions may not be well protected by it. Continuous biomonitoring provides another layer of protection for them.
1. Building the algorithm for early, pre-symptomatic DETECTION OF RESPIRATORY VIRAL INFECTION and for predicting eventual DETERIORATION. 2. Create an APP that AUTOMATES these algorithms and clearly REPORTS ACTIONABLE RESULTS to users, i.e., to medical professionals and citizens-at-large in near-real time. If alerted to a possible - and likely still asymptomatic - COVID-19 infection, they can self-isolate or be quarantined, get confirmatory COVID-19 testing done promptly, limit transmission to others, and stay safe knowing that if they are likely to deteriorate, the algorithm will alert the participants and their caregivers to the need to obtain medical attention promptly.
Study Type
OBSERVATIONAL
Enrollment
26
Emfit devices will be installed once after enrollment under each participant's mattress and left to record automatically without further intervention. The participants will wear their Biostrap wristbands consistently, ideally 24 hours a day, 7 days a week, for 2 months. A virus panel will be upon enrollment (baseline) and then every two weeks (± 3 days, or on the closest convenient sampling day if the LTCF is testing all residents on the same day) for a maximum of 5 times during the two-month period. Using polymerase chain reaction or next generation sequencing, the virus panel will detect COVID-19 and 12 other common respiratory viruses that may cause similar symptoms and similar biometric signatures. These include influenza A and B, parainfluenza types 1 through 4, respiratory syncytial virus, non-COVID coronavirus, rhinovirus, adenovirus, bocavirus and metapneumovirus.
Avalon Health & Rehabilitation Center
Pasco, Washington, United States
Proportion of quality signals obtained out of all monitoring time for each device
Feasibility assessment
Time frame: 8 weeks from first enrollment
Predictive characteristics of the algorithm for respiratory tract infection
Algorithm development, sensitivity, specificity, positive and negative predictive value at different lead times ahead of symptom onset
Time frame: 2 months
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