Observational Digital Biomarker Discovery in Respiratory Virus Challenge Studies

National Institute of Allergy and Infectious Diseases (NIAID)1,000 enrolled

Overview

Background: Respiratory viruses circulate throughout the year and around the globe. Wearable and sensor devices, like smartwatches, may be able to help monitor infectious diseases. Researchers want to use them to learn how respiratory viruses affect people in different ways. Objective: To use digital devices to collect data from participants in challenge studies that could indicate subtle changes in health during an infection that might otherwise go unnoticed. Eligibility: Healthy adults who have enrolled, were recently enrolled, or are scheduled to enroll in a challenge study. Design: Participants will stay at NIH for the duration of the challenge study (at least 9 days) and then will have outpatient follow-up visits (2-4). While at NIH, participants will wear a smartwatch at all times. It will record data like temperature, heart rate, breathing rate, and movements. Participants will have a smartphone that records at all times to listen for coughing and changes in voice. Participants will perform tasks every 4 hours during the daytime. They will record themselves coughing, breathing in deeply, and reading aloud. They will take videos of their face. They will play a game to test their reflexes and focus. They will measure their head temperature with their smartwatch. For outpatient visits, participants will use one smartphone and the smartwatch to complete the above tasks. Participants will be sent a smartwatch to wear at home at night to collect additional healthy data. Participation will last the duration of each challenge study, and may range from 10 weeks to 2 years.

Study Description: Wearable and sensor digital devices have the potential to be important tools in infectious diseases surveillance. In this study, digital devices will be used to evaluate responses before and after respiratory virus challenge on a separate NIH protocol. Participants recently enrolled, currently enrolled, or planned for enrollment in a challenge study are eligible. All devices will be worn and/or used during the inpatient hospitalization and at outpatient follow-up visits. Participants may be sent smartwatches at home to collect additional baseline or healthy data. Devices will collect data on coughing, speech, heart rate, heart rhythm, sweating, temperature, activity, and fatigue to identify digital biomarkers associated with respiratory virus infection. The correlation between digital device measurement data and clinical data, particularly on cough, will be determined. We hypothesize that sensor-collected data will correlate with symptom severity obtained by clinician assessment and participant report. We also hypothesize that digital biomarkers can predict influenza infection and can be used to develop a predictive model. Objectives: * Primary: 1. To correlate continuous cough sensor data to cough severity after challenge. 2. To develop a predictive model for mild-moderate influenza disease (MMID) and influenza infection using digital biomarkers * Secondary: To correlate continuous and noncontinuous vital sign sensor data to routine vital signs obtained by clinical staff. * Exploratory: To evaluate facial and body sensor data after challenge. Endpoints: Primary: 1. Cough quantity: -Continuous cough measurements 2. Infection * Defined as: * MMID (positive PCR for influenza and \>=1 symptoms) * Flu (positive PCR for influenza or convalescent four-fold increase in serum antibodies to the hemagglutinin (HA) or neuraminidase (NA) of the challenge virus and \>=1 symptoms) * Influenza infection (positive PCR for influenza) * Using Predictor variables: * Smartwatch photoplethysmography (PPG) determined heart rate * Smartwatch electrodermal activity (EDA) determined sweating * Smartwatch determined temperature * Smartwatch activity tracking * Smartwatch Electrocardiogram (ECG) monitoring * Facial video recording (including PPG) * Audio voice recording * Smartphone psychomotor vigilance testing (PVT) Secondary: Vital signs: 3. Heart rate 4. Respiratory rate 5. Temperature Exploratory: Facial and body sensor data via quantitative measures of: 6. Facial imaging 7. Voice recording 8. Activity/Sleep monitoring 9. Blood pressure (measured through facial imaging)

Eligibility

Sex: ALLMin age: 18 YearsMax age: 65 YearsHealthy volunteers:

Medical Language ↔ Plain English

* INCLUSION CRITERIA: In order to be eligible to participate in this study, an individual must meet all of the following criteria: 1. Able to provide informed consent. 2. Current, recent, or planned enrollment in a respiratory virus challenge study at the NIH Clinical Center. 3. Willing to wear devices as instructed. 4. Willing to participate in monitoring activities as instructed. 5. Willing to have monitoring data stored. 6. Willing to have monitoring data shared with protocol investigators at NIH, University of Washington, and University of Toronto. 7. Willing to have select clinical data from the challenge study such as vital signs, viral shedding, pulmonary function test and/or spirometry results, and clinical symptoms data shared with investigators at University of Washington and University of Toronto. EXCLUSION CRITERIA: An individual who meets any of the following criteria will be excluded from participation in this study: 1\. Any condition that, in the opinion of the investigator, contraindicates participation in this study. Co-enrollment guidelines: Participants must be co-enrolled, planned for co-enrollment, or recently enrolled in a challenge study. Co-enrollment in other studies is restricted but may take place after study staff notification and only with approval of the principal investigator or designee.

Outcomes

Primary Outcomes

To correlate continuous cough sensor data to cough severity after challenge.To develop a predictive model for MMID and asymptomatic influenza infection using digital biomarkers.

Cough is a known symptom of respiratory virus infections and can be quantified by objective measurements.Data from smart devices may be able to discern who gets sick with a respiratory virus and could be utilized as a diagnostic tool.

Time frame: minimum of 9 days inpatient

Secondary Outcomes

To correlate continuous and noncontinuous vital signs sensor data to routine vital signs obtained by clinical staff.

Vital signs are routinely measured in challenge studies and are also routinely collected from digital devices. Vital sign changes can be associated with respiratory virus infections.