Observational Digital Biomarker Discovery in Respiratory Virus Challenge Studies

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.

Detailed description

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. 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 may collect data on coughing, speech, heart rate, heart rhythm, sweating, and temperature 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:

1. To evaluate body sensor data after challenge. 2. To correlate digital biomarker data to biological biomarker data.

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 such as:

* Smartwatch photoplethysmography (PPG) determined heart rate * Smartwatch electrodermal activity (EDA) determined sweating * Smartwatch determined temperature * Smartwatch Electrocardiogram (ECG) monitoring * Audio voice recording

Secondary: Vital signs: 3. Heart rate 4. Respiratory rate 5. Temperature

Exploratory:

Correlations between digital biomarker data and biological biomarker data (e.g. antibody titers)

Primary outcome measures

• 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. [Time frame: minimum of 9 days inpatient]

Secondary outcome measures (1)

• To correlate continuous and noncontinuous vital signs sensor data to routine vital signs obtained by clinical staff. [Time frame: minimum of 9 days inpatient]

Eligibility criteria

• INCLUSION CRITERIA:

In order to be eligible to participate in this study, an individual must meet all of the following criteria:

• Able to provide informed consent.
• Current, recent, or planned enrollment in a respiratory virus challenge study at the NIH Clinical Center.
• Willing to wear devices as instructed.
• Willing to participate in monitoring activities as instructed.
• Willing to have monitoring data stored.
• Willing to have monitoring data shared with protocol investigators at NIH, University of Washington, and University of Toronto.
• 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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

United States · 1 center

• National Institutes of Health Clinical Center — Bethesda

Identifiers

NCT: NCT04772170 · 10000291 · 000291-I

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗