Natural History Study of COVID-19 Using Digital Wearables

Background: People with COVID-19 have varying degrees of illness. It can range from no or mild symptoms to critical illness and death. Some people with COVID-19 have long-term effects regardless of the severity of their disease initially. Researchers want to learn more to see if they can better predict where a person may fall on the illness spectrum. Objective: To follow and record symptoms of COVID-19 to see how it progresses in people and why some people stay sick longer than others. Eligibility: People ages 18-65 who received a COVID-19 positive test result in the 72 hours before their enrollment in the study. Design: Participants will complete a 30-minute baseline survey. They will answer questions about themselves and their health. Participants will get a digital wristband and temperature sensor in the mail. They will get instructions on how to set up and wear the devices. They will download a mobile application on their phone. The app will collect data from the devices. Participants will wear the wristband and sensor every day for the first month. Then they will wear the devices for a total of 40 days over the next 5 months. On the days they wear the devices, they will answer a 2-question health survey via the app. Participants will answer a 20-minute online survey about their health every 30 days. If participants are hospitalized, a family member or close friend will be asked to complete a brief 7-minute online survey about their hospital stay and treatment. Participants will be sent alerts and reminders throughout the study. Participation will last for 6 months.

Study Description: COVID-19 patients experience varying degrees of illness. Factors associated with prolonged illness remain unknown especially in non-hospitalized patients. This study uses digital wearables to collect high-resolution physiological data to understand the clinical course of COVID-19 in patients with a positive COVID-19 diagnosis. We hypothesize that wearables-based physiological data are associated with COVID-19 post-acute sequelae. Objectives: To identify digital wearables-based physiological data that are associated with COVID-19 post-acute sequelae. Endpoints: Primary endpoint: Long COVID-19 defined as \>=1 symptom at 3 weeks beyond first symptom onset or test positivity, whichever comes first. Secondary endpoint: Chronic COVID-19 defined as \>=1 symptom at 12 weeks beyond first symptom onset or test positivity, whichever comes first.