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

NCT06207929 | Completed

• 1 other identifier: WAVE Study
• Study Type: observational
• Target: 18,157
• Locations: 1 country
• Sites: 1

Brief 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 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.

Conditions

Influenza, Human; COVID-19; Influenza A; Influenza B; Respiratory Syncytial Virus (RSV)

Keywords

Flu; Influenza; RSV; COVID; Wearable

Outcome Measures

Primary Outcomes (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.

  Through study completion, approximately 10 months

Secondary Outcomes (1)

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

  Through study completion, approximately 10 months

Study Arms (1)

Study Population

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

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

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

You may qualify if:

• 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

You may not qualify if:

• 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)

Sponsors & Collaborators

• Evidation Health: lead
• Biomedical Advanced Research and Development Authority: collaborator

Study Sites (1)

Evidation Health

San Mateo, California, 94402, United States

Location

Related Publications (10)

• 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.

  PMID: 36890264 BACKGROUND

• 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.

  PMID: 29206909 BACKGROUND

• 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.

  PMID: 35759279 BACKGROUND

• 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.

  PMID: 35552722 BACKGROUND

• 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.

  PMID: 33506230 BACKGROUND

• 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.

  PMID: 36951890 BACKGROUND

• 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.

  BACKGROUND

• 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.

  PMID: 35480626 BACKGROUND

• 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.

  PMID: 36963907 BACKGROUND

• 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.

  PMID: 36050372 BACKGROUND

Related Links

• COVID Data Tracker. Centers for Disease Control and Prevention
• RESP-NET Interactive Dashboard. Centers for Disease Control and Prevention

Biospecimen

Retention: SAMPLES WITHOUT DNA

All valid specimens will be tested using RT-PCR via the Abbott Alinity m Resp-4-Plex assay. A subset of individuals selected by the study team will be asked to provide saliva samples after enrolling in the study using the Spectrum MAXSwab Saliva Collection Device. Saliva samples may be shipped to another lab for processing and may be stored indefinitely. Valid saliva samples may, or may not, be tested for IgA and IgG at a to be determined lab.

MeSH Terms

Conditions

Influenza, Human; COVID-19

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Orthomyxoviridae Infections; RNA Virus Infections; Virus Diseases; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; Lung Diseases

Study Officials

• Ernesto Ramirez, PhD

  Evidation Health

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: December 20, 2023
• First Posted: January 17, 2024
• Study Start: January 21, 2024
• Primary Completion: August 7, 2024
• Study Completion: August 7, 2024
• Last Updated: September 5, 2024

Record last verified: 2024-09

Locations

US (1)