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Influenza, HumanWAVENCT06207929

Wearable Assisted Viral Evidence (WAVE) Study A Decentralized, Prospective Study Exploring the Relationship Between Passively-collected Data From Wearable Activity Devices and Respiratory Viral Infections

An observational study of Influenza, Human and COVID-19, run by Evidation Health at 1 site in United States.

Completed

Finished. The study has ended and is not enrolling. Results may be posted on the official record.

Official record
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Trial summary

The goal of this decentralized, observational study is to enroll and observe adults in the contingent United States during the 2023-2024 flu season. The main study objectives are to create a dataset of paired wearable data, self-reported symptoms, and respiratory viral infection (RVI) from PCR testing during the… Read more about this study

Who is it for?
Ages 18 years and olderHealthy volunteers can take part
Conditions the study is for
Influenza, Human, COVID-19, Influenza A
How many people
18,157 participants
Where
1 siteUnited States
Study dates
21 Jan 2024to 7 Aug 2024
Phase
Observational
Are there results?
None posted in the registry

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Study population: Adult participants (ages 18+) who reside in the contiguous United States

Who may be able to join

  • Lives in the United States
  • Speaks, reads, and understands English
  • Currently owns and uses a consumer wearable device (Apple Watch, Garmin, or Fitbit) with necessary step and heart rate data at minimum or willing to wear a study-provided device and download the Fitbit app
  • Willing to connect their wearable device to the Evidation platform and wear it daily for at least 10 hours for the duration of the study
  • Owns a smartphone with Apple iOS 15 installed or higher OR Android version 9.0 installed or higher or willing to update
  • Willing to respond to daily and weekly questionnaires for a 10-week period
  • Willing to complete at-home nasal swab tests and return the nasal swab samples within 24 hours of being asked to complete it
  • Meets data density requirements for wearable devices

Who cannot join

  • Self reported diagnosis of both flu and COVID by a healthcare professional or using an at-home test in the past 3 months
  • Currently enrolled in another interventional study to prevent or treat COVID-19 or another flu-related program being conducted by Evidation (individuals currently participating in Evidation's FluSmart program will be told that their participation will be paused)
  • Has a primary mailing address that is a P.O box, Army Post Office (APO), Fleet Post Office (FPO), or Diplomatic Post Office (DPO) address, or U.S. military base located overseas, or U.S. territories (Puerto Rico, U.S. Virgin Islands, Guam, Northern Mariana Island, or American Samoa)

Trial locations and contacts

1 site in 1 country.

United States1 site

  • Evidation Health

    San Mateo, California, 94402

Other trials in United States

About this study

The goal of this decentralized, observational study is to enroll and observe adults in the contingent United States during the 2023-2024 flu season. The main study objectives are to create a dataset of paired wearable data, self-reported symptoms, and respiratory viral infection (RVI) from PCR testing during the 2023-2024 flu season and to develop algorithm that is able to accurately classify asymptomatic and symptomatic RVI and understand the algorithm's performance metrics.

Keywords
Flu, Influenza, RSV, COVID, Wearable
Medical subject headings
Influenza, Human, COVID-19

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

Study groups in NCT06207929
Study groupRoleWhat they receive
Study PopulationAdult participants (ages 18+) who reside in the contiguous United States

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. The primary objectives are to develop a dataset of paired wearable data, self-reported symptoms, and confirmed respiratory viral infection and use the dataset to develop an algorithm to classify asymptomatic/symptomatic RVIs

    This study will gather wearable device data, including heart rate, sleep, activity, and other data types from commercially available wearable activity trackers and smartwatches (e.g. Apple Watch, Fitbit, Garmin devices), as well as self-reported data related to the experience of symptoms associated with respiratory viral infections, and pair this data with the results from PCR tests of serial at-home nasal swabs for SARS-CoV-2, Influenza A, Influenza B, and respiratory syncytial virus (RSV). This data will be used to determine if these data types can be used to develop an algorithm for classifying asymptomatic and symptomatic RVI. Algorithm performance will be assessed across a variety of dimensions including ROC AUC, sensitivity, specificity, PPV, and NPV.

    Measured: Through study completion, approximately 10 months

Secondary outcomes (1)

  1. The secondary objective of this observational study is to determine if algorithm performance differs across various demographic groups

    We will test algorithm performance for various different groups of participants to better understand if the algorithm performs difference depending on participant demographics. For example, we will test for performance metrics across different subgroups related to gender, ethnicity, and age. For each subgroup, we will report on ROC AUC, sensitivity, specificity, PPV, and NPV. as appropriate.

    Measured: Through study completion, approximately 10 months

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted17 Jan 2024
  2. Study start21 Jan 2024
  3. Primary completion7 Aug 2024
  4. Study completion7 Aug 2024

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Other
Time perspective
Prospective
Enrolment
18,157 participants (actual)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06207929
Sponsor's protocol ID
WAVE Study
Acronym
WAVE
Status last verified
Sep 2024
First submitted
20 Dec 2023
Last updated
5 Sep 2024
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Undecided: We have provisions in our study protocol and consent to share Coded Study Data with approved external research partners. The sharing process is not yet finalized.

Publications

  • Wiemken TL, Khan F, Puzniak L, Yang W, Simmering J, Polgreen P, Nguyen JL, Jodar L, McLaughlin JM. Seasonal trends in COVID-19 cases, hospitalizations, and mortality in the United States and Europe. Sci Rep. 2023 Mar 8;13(1):3886. doi: 10.1038/s41598-023-31057-1.

    PubMed 36890264

  • Tokars JI, Olsen SJ, Reed C. Seasonal Incidence of Symptomatic Influenza in the United States. Clin Infect Dis. 2018 May 2;66(10):1511-1518. doi: 10.1093/cid/cix1060.

    PubMed 29206909

  • Temple DS, Hegarty-Craver M, Furberg RD, Preble EA, Bergstrom E, Gardener Z, Dayananda P, Taylor L, Lemm NM, Papargyris L, McClain MT, Nicholson BP, Bowie A, Miggs M, Petzold E, Woods CW, Chiu C, Gilchrist KH. Wearable Sensor-Based Detection of Influenza in Presymptomatic and Asymptomatic Individuals. J Infect Dis. 2023 Apr 12;227(7):864-872. doi: 10.1093/infdis/jiac262.

    PubMed 35759279

  • Mezlini A, Shapiro A, Daza EJ, Caddigan E, Ramirez E, Althoff T, Foschini L. Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors. JAMA Netw Open. 2022 May 2;5(5):e2211958. doi: 10.1001/jamanetworkopen.2022.11958.

    PubMed 35552722

  • Shapiro A, Marinsek N, Clay I, Bradshaw B, Ramirez E, Min J, Trister A, Wang Y, Althoff T, Foschini L. Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data. Patterns (N Y). 2020 Dec 13;2(1):100188. doi: 10.1016/j.patter.2020.100188. eCollection 2021 Jan 8.

    PubMed 33506230

  • Hunter V, Shapiro A, Chawla D, Drawnel F, Ramirez E, Phillips E, Tadesse-Bell S, Foschini L, Ukachukwu V. Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study. J Med Internet Res. 2023 Mar 23;25:e41050. doi: 10.2196/41050.

    PubMed 36951890

  • Merrill MA, Safranchik E, Kolbeinsson A, et al. Homekit2020: A Benchmark for Time Series Classification on a Large Mobile Sensing Dataset with Laboratory Tested Ground Truth of Influenza Infections. Conference on Health, Inference, and Learning PMLR 209:207-228. 2023 Jun.

  • Mayer C, Tyler J, Fang Y, Flora C, Frank E, Tewari M, Choi SW, Sen S, Forger DB. Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression. Cell Rep Med. 2022 Apr 19;3(4):100601. doi: 10.1016/j.xcrm.2022.100601. eCollection 2022 Apr 19.

    PubMed 35480626

  • Nestor B, Hunter J, Kainkaryam R, Drysdale E, Inglis JB, Shapiro A, Nagaraj S, Ghassemi M, Foschini L, Goldenberg A. Machine learning COVID-19 detection from wearables. Lancet Digit Health. 2023 Apr;5(4):e182-e184. doi: 10.1016/S2589-7500(23)00045-6. No abstract available.

    PubMed 36963907

  • Shandhi MMH, Cho PJ, Roghanizad AR, Singh K, Wang W, Enache OM, Stern A, Sbahi R, Tatar B, Fiscus S, Khoo QX, Kuo Y, Lu X, Hsieh J, Kalodzitsa A, Bahmani A, Alavi A, Ray U, Snyder MP, Ginsburg GS, Pasquale DK, Woods CW, Shaw RJ, Dunn JP. A method for intelligent allocation of diagnostic testing by leveraging data from commercial wearable devices: a case study on COVID-19. NPJ Digit Med. 2022 Sep 1;5(1):130. doi: 10.1038/s41746-022-00672-z.

    PubMed 36050372

Questions about this trial

What is this clinical trial studying?

An observational study of Influenza, Human and COVID-19, run by Evidation Health at 1 site in United States.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 8 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: finished, as of the sponsor's last update on 5 Sep 2024. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

The primary objectives are to develop a dataset of paired wearable data, self-reported symptoms, and confirmed respiratory viral infection and use the dataset to develop an algorithm to classify asymptomatic/symptomatic RVIs (time frame: Through study completion, approximately 10 months). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06207929, which also lists 10 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Sep 2024.

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WAVE Clinical Trial NCT06207929 | AzTrials