Acute Respiratory Illness Surveillance (AcRIS) With Mobile Application in a Low-Interventional Decentralized Study.

NCT04748445 | Completed Results

• 1 other identifier: X9001293
• Study Type: observational
• Target: 9,151
• Locations: 1 country
• Sites: 1

Brief Summary

The purpose of the AcRIS study is to obtain data to characterize the relationship between symptoms and voice features for (reverse transcription polymerase chain reaction (RT-PCR) confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza virus, or Respiratory Syncytial Virus (RSV) positive participants with acute viral respiratory illness. This data will be used as the basis to build voice and symptom algorithm(s) for detection and monitoring of these illnesses. This would benefit vaccine development across several key disease areas, including SARS-CoV-2, influenza virus and RSV. The study also models concepts of more efficient "flexible" clinical trials involving not only voice capture, but also web-based participant recruitment, enhanced participant engagement, and remote sample collection that could make future clinical studies more efficient. The clinical data obtained in this observational study could provide the documentation of the technology's performance needed to enable its deployment in future interventional studies.

Conditions

Healthy

Keywords

Covid-19; Covid 19; Coronavirus; SARS-CoV-2; Flu; Influenza; RSV; Respiratory syncytial virus; Respiratory illness; Acute respiratory illness; remote trial; voice; AcRIS

Outcome Measures

Primary Outcomes (10)

• Change From Baseline in Self-Reported Symptom Scores From Well-to-Sick State Through Day 56

  Symptoms (fever, cough, difficult breathing, fatigue, runny nose, stuffy/blocked nose, sore throat, loss of taste/smell, chills, muscle pain, diarrhea, vomiting, headache, nausea, rigors, wheezing) recorded at least once daily in e-diary for 8 weeks \& rated 0:none to 4:severe for fever \& 0:none to 7:severe for other symptoms. Total symptom score=sum of all symptom scores in a recording session \& mean of daily total symptom score=average across available sessions for each day, range=0 to 109, higher value=more severe total symptoms. Baseline=average of values up to 7 days before 1st occurrence of new/increased symptoms. If no data in 7 days, average of endpoint values for closest 3 days prior to 7 days used as baseline. Linear mixed effect model used for analysis for change from baseline in each symptom versus day during well to sick period, with slope (without intercept) included as fixed effects and random effects. Fixed effect of slope, as population level estimate, was reported.

  Baseline up to Day 56

• Change From Baseline in Voice Features (AHH_Max Phonation Time, EE_Jitter Local Absolute, MM_Jitter Local Absolute) Values From Well-to-Sick State Through Day 56

  Participants recorded voice features such as pitch, jitter once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Max Phonation Time: duration that sound is held for. Jitter Local Absolute: average absolute difference between consecutive periods. Indicates how unsteady the pitch is across neighboring glottal pulses. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Feature (Cepstral Peak Prominence, Harmonicity, MFCC Mean, MFCC Std, SNR, Shimmer Local dB, Spectral Flatness, Third Octave Band, and VLHR) Values From Well-to-Sick State Through Day 56

  Harmonicity, flatness, shimmer recorded and assessed by phonemes: 'eee' and 'mmm' for 4 seconds, "ahh" sustained and 5-sentence reading passage. Cepstral Peak Prominence: voice quality measure. Harmonicity: degree of periodicity in signal. mel frequency cepstral coefficients (MFCC) mean: quantifies shape of spectrum. MFCC std: quantifies variation in spectral shape over time. Signal-to-noise ratio (SNR): how loud signal is compared to background. Shimmer Local dB: average absolute difference between amplitudes of consecutive periods (how unsteady sound intensity is across neighboring glottal pulses). Spectral Flatness: quantifies how tone-like a signal is based on spectral distribution. Third Octave Band: energy in 200 Hz third octave band relative to total. VLHR: degree of nasality. Linear mixed effect model used for analysis. Fixed effect of slope, as population level estimate is reported. Individual exponential factors for data presented have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Feature (Coefficient of Variation, Mel Frequency Cepstral Coefficients (MFCC) 1st Order Delta, MFCC 2nd Order Delta) Values From Well-to-Sick State Through Day 56

  Voice features were recorded once daily in an electronic diary for 8 weeks. Assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Coefficient of Variation of F0: measures variation in pitch over time. MFCC 1st order delta: time-averaged estimate of first derivate of the MFCCs. MFCC 2nd order delta: time-averaged estimate of the second derivative of the MFCCs. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (EE_Entropy, MM_Entropy) Values From Well-to-Sick State Through Day 56

  Participants recorded voice features such as entropy once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Entropy: Shannon entropy of the spectral distribution. Quantifies tonailty similar to spectral flatness. "EE\_Entropy" and "MM\_Entropy" refer to this same measure computed on the "eee" and "mmm" phonemes, respectively. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (Formant and Formant Bandwidth) Values From Well-to-Sick State Through Day 56

  Participants recorded voice features once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Formant: frequency at which the vocal tract produces an acoustic resonance. Formant Bandwidth: the spectral width of the acoustic resonance. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (EE_Voiced Frames, MM_Voiced Frames) Values From Well-to-Sick State Through Day 56

  Participants recorded voice features once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. The voiced frames rate indicates how much of the sound is voiced. EE and MM refer to the sounds on which the measure is computed. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (EE_Jitter Local, MM_Jitter Local) Values From Well-to-Sick State Through Day 56

  Voice features such as jitter were recorded once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Jitter Local: average absolute difference between consecutive periods divided by the average period as a percentage. Indicates how unsteady the pitch is across neighboring glottal pulses. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (EE_Shimmer Local, MM_Shimmer Local) Values From Well-to-Sick State Through Day 56

  Voice features such as shimmer were once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Shimmer Local: average absolute difference between the amplitudes of consecutive periods divided by the average amplitude as a percentage. Indicates how unsteady the sound intensity is across neighboring glottal pulses. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor in addition to values mentioned. Individual exponential factors have been mentioned in respective row title.

  Baseline up to Day 56

• Change From Baseline in Voice Features (READ_Speaking Rate) Values From Well-to-Sick State Through Day 56

  Participants recorded voice features once daily in an electronic diary for 8 weeks. Voice assessments were done by 2 phonemes: 'eee' and 'mmm' for 4 seconds (minimum 3 seconds), 1 phoneme: "ahh" sustained (as long as possible) and a 5-sentence reading passage. Baseline was average of endpoint values up to 7 days before first occurrence of new/increased symptoms. If participant had no data in 7 days, average of endpoint values for closest 3 days prior to these 7 days was used as baseline. Linear mixed effect model was used for analysis for change from baseline in each voice feature versus day during the well to sick period, with slope (without intercept) included as fixed effects and random effects. The fixed effect of the slope, as the population level estimate, was reported. The data given has exponential factor (i.e. LSM\*10\^-2, SE\*10\^-3) in addition to values mentioned.

  Baseline up to Day 56

Secondary Outcomes (7)

• Percentage of Compliant Days in Total Days of Symptoms and Total Days of Voice Recordings Entered in the Electronic Diary

  Day 1 up to Day 56

• Percentage of Quality Voice Recordings

  Day 1 up to Day 56

• Percentage of Participants With a Positive Self-Swab Result for SARS-CoV-2 and/or Influenza and/or RSV

  Day 2 up to Day 43

• Percentage of Participants Who Administered Self-swab 1 and Self-swab 2

  Day 2 up to Day 43

• Number of Days Between Reporting Symptoms and Recording Swab 2 in the Electronic-Diary

  Day 2 Up to Day 43

Study Arms (1)

All participants

Diagnostic Test: SARS-CoV-2/Influenza/RSV RT-PCR

Interventions

SARS-CoV-2/Influenza/RSV RT-PCR DIAGNOSTIC_TEST

nasal swab

All participants

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

Planned enrollment of approximately 8700 participants 18 years of age or older in order to have a total of N of 100 participants with (1) confirmed negative SARS-CoV-2, RSV or Influenza RT-PCR (swab #1) and (2) confirmed positive SARS-CoV-2 RT-PCR, influenza virus or RSV (swab #2) symptomatic completers.

You may qualify if:

• Participants are eligible to be included in the study only if all of the following criteria apply:
• Age and Sex:
• Male or female participants ≥18 years of age (or the minimum state specific age of consent if \>18), at Screening visit.
• Type of Participant and Disease Characteristics:
• Participants who are willing and able to comply with daily symptom and voice assessments on the electronic diary application and other study procedures, including self-collection of nasal swabs.
• Expected to be available for the duration of the study.
• Informed Consent:
• \. Capable of giving signed informed consent

You may not qualify if:

• Participants are excluded from the study if any of the following criteria apply:
• Participants who self-report any medical condition, recreational substance use, or medication use which would prevent them from completing study tasks or impair the providing of informed consent, or in the investigator's judgment, make the participant inappropriate for the study.
• Prior/Concomitant Therapy:
• Participants who have been vaccinated with COVID-19 vaccine or are planning to get vaccinated during study participation.
• Participants can continue to use all other prescription or non-prescription medications.
• Prior/Concurrent Clinical Study Experience:
• Previous vaccination with any licensed or investigational RSV vaccine or are planning to get vaccinated during study participation.
• Previous administration with an investigational drug within 30 days of enrollment (or as determined by the local requirement) or planning to participate in an interventional trial during study conduct.
• Diagnostic Assessments:
• Screening diagnostic assessments are not required for eligibility purposes.
• Investigator site staff or Pfizer employees directly involved in the conduct of the study, site staff otherwise supervised by the investigator including vendors, and their respective family members.
• Participants who use a mobile device that does not meet the minimum requirements of the Electronic diary.
• Participants who have previously been enrolled in the study cannot be re-enrolled.

Sponsors & Collaborators

• Pfizer: lead

Study Sites (1)

Ochsner Clinic Foundation

New Orleans, Louisiana, 70121, United States

Location

Related Publications (2)

• Chappie K, Kell S, Qi D, Selig J, Christakis Y, Moreno X, Severson J, Best A, Wacnik P, Santamaria M, Zhang Y, Fry BA, Mather RJ. Comparing Phoneme Speech Recordings and Acoustic App Data Capture Experience for Android and iOS Mobile Device Users in the Large Decentralized AcRIS Study. J Voice. 2025 Jun 23:S0892-1997(25)00201-2. doi: 10.1016/j.jvoice.2025.05.016. Online ahead of print.

  PMID: 40555587 DERIVED

• Santamaria M, Christakis Y, Demanuele C, Zhang Y, Tuttle PG, Mamashli F, Bai J, Landman R, Chappie K, Kell S, Samuelsson JG, Talbert K, Seoane L, Mark Roberts W, Kabagambe EK, Capelouto J, Wacnik P, Selig J, Adamowicz L, Khan S, Mather RJ. Longitudinal voice monitoring in a decentralized Bring Your Own Device trial for respiratory illness detection. NPJ Digit Med. 2025 Apr 11;8(1):202. doi: 10.1038/s41746-025-01584-4.

  PMID: 40210993 DERIVED

Related Links

• To obtain contact information for a study center near you, click here.

Biospecimen

Retention: SAMPLES WITHOUT DNA

SARS-CoV-2/Influenza/RSV RT-PCR

MeSH Terms

Conditions

COVID-19; Coronavirus Infections; Influenza, Human

Condition Hierarchy (Ancestors)

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

Results Point of Contact

• Title: Pfizer ClinicalTrials.gov Call Center
• Organization: Pfizer Inc.

ClinicalTrials.gov_Inquiries@pfizer.com

1-800-718-1021

Study Officials

• Pfizer CT.gov Call Center

  Pfizer

  STUDY DIRECTOR

Publication Agreements

• PI is Sponsor Employee: No
• Restriction Type: OTHER
• Restrictive Agreement: Yes

Study Design

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

Study Record Dates

• First Submitted: February 5, 2021
• First Posted: February 10, 2021
• Study Start: April 12, 2021
• Primary Completion: April 22, 2022
• Study Completion: April 22, 2022
• Last Updated: February 23, 2024
• Results First Posted: February 23, 2024

Record last verified: 2024-02

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)