Use of Wearable Sensors for Early Detection and Tracking of Viral Respiratory Tract Infections

NCT05290792 | Completed

• 1 other identifier: 2022-7591
• Study Type: interventional
• Target: 56
• Locations: 1 country
• Sites: 1

Brief Summary

Viral respiratory tract infections (VRTI) are among the most common human illnesses, impacting billions globally. There is an unmet need to identify novel ways to detect, treat and prevent their spread. New wearable devices could address this need, using special biosensors worn by patients. This is a single centre, controlled, before and after, longitudinal, clinical trial. Participants will receive FluMist, a live attenuated influenza vaccine, which will act as a proxy to a viral respiratory tract infection and create a very minor response to the immune system. Vital signs and activity levels will be monitored continuously using wearable biosensors for 7 days prior to and 7 days following, along with symptom tracking and blood tests to measure immune responses. Artificial intelligence (AI) and machine learning (ML) algorithms will be used to analyse the data. AI and ML will identify subtle changes in vital signs and activity levels from the immune response to respiratory viruses. These data will help develop future methods to address important public health questions related to respiratory virus detection, containment and management. The purpose of this study is to explore whether wearable sensors can detect, track the progress and recovery from viral respiratory tract infection.

Conditions

Viral Respiratory Tract Infection; Influenza

Outcome Measures

Primary Outcomes (7)

• Changes in heart rate (in beats per minute)

  Intra-individual changes in heart rate before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in heart rate variability (in milliseconds)

  Intra-individual changes in heart rate variability before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in respiratory rate (in breaths per minute)

  Intra-individual changes in respiratory rate before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in skin temperature (in degrees Celsius)

  Intra-individual changes in skin temperature before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in acceleration (meters/second^2)

  Intra-individual changes in acceleration before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in blood pressure (in mmHg)

  Intra-individual changes in blood pressure before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

• Changes in oxygen saturation (SpO2 in %)

  Intra-individual changes in oxygen saturation before and after receipt of the Live Attenuated Influenza Vaccine measured by wearable sensors.

  14 days

Study Arms (1)

Intra-individual changes of physiological and activity parameters

OTHER

Participants will be administered FluMist (live attenuated influenza vaccine) to induce a low grade VRTI (Day 0). Participants will be monitored in the 7 days prior and 7 days after vaccination via symptom questionnaires, blood draws, stair tests and vital sign monitoring from wearable sensors. Each participant will serve as their own control, relying on the baseline measurements obtained over the 7-day period prior to inoculation.

Biological: Administration of FluMist (Live Attenuated Influenza Vaccine)

Interventions

Administration of FluMist (Live Attenuated Influenza Vaccine) BIOLOGICAL

Participants will received the intranasal FluMist vaccine that will serve as a proxy for a viral respiratory tract infection and trigger a mild immune response.

Intra-individual changes of physiological and activity parameters

Eligibility Criteria

• Age: 18 Years - 59 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64)

You may qualify if:

• Men or women aged 18-59 years
• Did not receive the 2021-2022 seasonal influenza vaccine
• Not planning to get another vaccine during the 14-day observation period.

You may not qualify if:

• PCR-confirmed VRTI at screening
• Any infectious symptoms (fever, cough, rhinorrhea, sore throat, diarrhea, loss of smell or taste) within the previous 7 days
• Any chronic medical condition;
• Obesity (BMI\>35 kg/m2);
• Any prescription drug other than oral contraceptives or routine and stable dose medications;
• Contraindication to LAIV
• Current smoker or ex-smoker with \>20 pack years of smoking
• Recreational drug use
• Self-reported history of substance abuse
• Pregnant or attempting to become pregnant
• Guillain-Barré syndrome (GBS) or BGS-like episode has occurred within 6 weeks of any prior influenza vaccination
• Immunocompromised
• People with severe asthma or medically attended wheezing in the 7 days prior to the proposed date of vaccination.

Sponsors & Collaborators

• Emily McDonald: lead
• Canadian Institutes of Health Research (CIHR): collaborator
• Université de Montréal: collaborator

Study Sites (1)

Centre for Innovative Medicine - McGill University Health Centre

Montreal, Quebec, H4A 3J1, Canada

Location

Related Publications (11)

• Molinari NA, Ortega-Sanchez IR, Messonnier ML, Thompson WW, Wortley PM, Weintraub E, Bridges CB. The annual impact of seasonal influenza in the US: measuring disease burden and costs. Vaccine. 2007 Jun 28;25(27):5086-96. doi: 10.1016/j.vaccine.2007.03.046. Epub 2007 Apr 20.

  PMID: 17544181 BACKGROUND

• Schanzer DL, McGeer A, Morris K. Statistical estimates of respiratory admissions attributable to seasonal and pandemic influenza for Canada. Influenza Other Respir Viruses. 2013 Sep;7(5):799-808. doi: 10.1111/irv.12011. Epub 2012 Nov 5.

  PMID: 23122189 BACKGROUND

• Casadevall A, Pirofski LA. The damage-response framework of microbial pathogenesis. Nat Rev Microbiol. 2003 Oct;1(1):17-24. doi: 10.1038/nrmicro732.

  PMID: 15040176 BACKGROUND

• Menni C, Valdes AM, Freidin MB, Sudre CH, Nguyen LH, Drew DA, Ganesh S, Varsavsky T, Cardoso MJ, El-Sayed Moustafa JS, Visconti A, Hysi P, Bowyer RCE, Mangino M, Falchi M, Wolf J, Ourselin S, Chan AT, Steves CJ, Spector TD. Real-time tracking of self-reported symptoms to predict potential COVID-19. Nat Med. 2020 Jul;26(7):1037-1040. doi: 10.1038/s41591-020-0916-2. Epub 2020 May 11.

  PMID: 32393804 BACKGROUND

• Yanes-Lane M, Winters N, Fregonese F, Bastos M, Perlman-Arrow S, Campbell JR, Menzies D. Proportion of asymptomatic infection among COVID-19 positive persons and their transmission potential: A systematic review and meta-analysis. PLoS One. 2020 Nov 3;15(11):e0241536. doi: 10.1371/journal.pone.0241536. eCollection 2020.

  PMID: 33141862 BACKGROUND

• Watson J, Whiting PF, Brush JE. Interpreting a covid-19 test result. BMJ. 2020 May 12;369:m1808. doi: 10.1136/bmj.m1808. No abstract available.

  PMID: 32398230 BACKGROUND

• Li X, Dunn J, Salins D, Zhou G, Zhou W, Schussler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP. Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol. 2017 Jan 12;15(1):e2001402. doi: 10.1371/journal.pbio.2001402. eCollection 2017 Jan.

  PMID: 28081144 BACKGROUND

• Radin JM, Wineinger NE, Topol EJ, Steinhubl SR. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Lancet Digit Health. 2020 Feb;2(2):e85-e93. doi: 10.1016/S2589-7500(19)30222-5. Epub 2020 Jan 16.

  PMID: 33334565 BACKGROUND

• Emery JC, Russell TW, Liu Y, Hellewell J, Pearson CA; CMMID COVID-19 Working Group; Knight GM, Eggo RM, Kucharski AJ, Funk S, Flasche S, Houben RM. The contribution of asymptomatic SARS-CoV-2 infections to transmission on the Diamond Princess cruise ship. Elife. 2020 Aug 24;9:e58699. doi: 10.7554/eLife.58699.

  PMID: 32831176 BACKGROUND

• Quer G, Radin JM, Gadaleta M, Baca-Motes K, Ariniello L, Ramos E, Kheterpal V, Topol EJ, Steinhubl SR. Wearable sensor data and self-reported symptoms for COVID-19 detection. Nat Med. 2021 Jan;27(1):73-77. doi: 10.1038/s41591-020-1123-x. Epub 2020 Oct 29.

  PMID: 33122860 BACKGROUND

• Hadid A, McDonald EG, Cheng MP, Papenburg J, Libman M, Dixon PC, Jensen D. The WE SENSE study protocol: A controlled, longitudinal clinical trial on the use of wearable sensors for early detection and tracking of viral respiratory tract infections. Contemp Clin Trials. 2023 May;128:107103. doi: 10.1016/j.cct.2023.107103. Epub 2023 Mar 29.

  PMID: 37147083 DERIVED

MeSH Terms

Conditions

Influenza, Human

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Orthomyxoviridae Infections; RNA Virus Infections; Virus Diseases; Respiratory Tract Diseases

Study Officials

• Emily G McDonald, MD

  McGill University Health Centre/Research Institute of the McGill University Health Centre

  PRINCIPAL INVESTIGATOR

• Dennis Jensen, PhD

  McGill University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: SCREENING
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Associate Professor of Medicine, MD MSc FRCPC

Model Details: Single centre, controlled, before and after, longitudinal, intra-individual assessment

Study Record Dates

• First Submitted: February 25, 2022
• First Posted: March 22, 2022
• Study Start: December 10, 2021
• Primary Completion: October 31, 2022
• Study Completion: October 31, 2022
• Last Updated: March 25, 2025

Record last verified: 2023-10

Data Sharing

• IPD Sharing: Will not share

Locations

CA (1)