Community-Acquired Respiratory Tract Infection, Covid19
Conditions
Keywords
COVID-19, wearables, biometric data
Brief summary
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.
Detailed description
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.
Interventions
DEVICEObservational measurement of biometric data. No change to health care provided.
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.
Sponsors
Health Stream Analytics, LLC
Study design
Observational model
ECOLOGIC_OR_COMMUNITY
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
Inclusion criteria
* Residents and staff members of U.S. LTCFs where COVID-19 transmission is actively occurring. The LTCF medical director must agree to enroll the LTCF, and each participant must have the capacity to agree and sign consent.
Exclusion criteria
* Current atrial fibrillation. * NB: Paroxysmal atrial fibrillation is permitted if the participant is in atrial fibrillation less than 50% of the day on most days. * Pacemaker in place. * Known active infection other than COVID-19. * Dementia
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proportion of quality signals obtained out of all monitoring time for each device | 8 weeks from first enrollment | Feasibility assessment |
| Predictive characteristics of the algorithm for respiratory tract infection | 2 months | Algorithm development, sensitivity, specificity, positive and negative predictive value at different lead times ahead of symptom onset |
Countries
United States
Outcome results
None listed