COVID-19 Observational Study

Coronaviruses are a group of viruses that can cause mild respiratory infections, such as the common cold. They can, however, also be potentially lethal, as seen in cases of severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS) and the recent Coronavirus disease 2019 (COVID-19). 

COVID-19 presents with early onset symptoms such as fever, cough, dyspnea and shortness of breath (Mayo Clinic) within 2 to 14 days of exposure. According to the CDC, the virus is thought to spread primarily from person to person through close contact or contact with surfaces contaminated with respiratory droplets produced by an infected individual. While individuals are thought to be most contagious when symptomatic, it is believed that COVID-19 may spread prior to onset of symptoms, leading to an emphasis on early identification, intervention and implementation of source control (Interim Infection Prevention and Control Recommendations, CDC). 

Physiological processes including thermoregulation, respiratory rate and heart rate are regulated via the autonomic nervous system, which is responsible for maintaining homeostatic balance. A study performed at Stanford University (Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information, 2017) found that fitness monitors and other wearable biosensors can determine when the individual’s heart rate, skin temperature and other measures are abnormal, indicating possible illness. Another study by Lancet Digital Health (Harnessing Wearable Device Data to Improve State-Level Real-Time Surveillance of Influenza-like Illness in USA: A population Based Study, 2020) found that biometric data from physiological trackers may improve real-time and geographically refined influenza surveillance which may be vital to enact timely outbreak response measures.  In addition, heart rate variability, nocturnal oxygen saturation and an increase in cardiac output can be valuable measures prior to symptomatic respiratory tract viral infection.  Abrupt changes in these biometrics, measured by Biostrap, may provide early indication of non-specific exposure and imminent illness prior to the onset of symptoms.

According to the CDC, individuals are most contagious when they are the most symptomatic. Through an analysis of relative change at the level of the individual, this data may provide value (when utilized in conjunction with validated diagnostic assessments) to understand severity and individual contagion factor.  Similarly, a positive biometric trend change, indicating a return to baseline, may provide a method to gauge improvements, although validated diagnostic testing would be necessary.