COVID-19 Respiratory InfectionNCT04623047
Infection Watch Study
An observational study of COVID-19 Respiratory Infection and Respiratory Syncytial Virus Infections, run by Duke University at 1 site in United States.
Trial summary
This study will reach out to patients who have undergone diagnostic testing for the following respiratory illnesses from January 1st, 2018 to July 9th, 2023: COVID-19, Influenza, Rhinovirus, and Respiratory Syncytial Virus. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- COVID-19 Respiratory Infection, Respiratory Syncytial Virus Infections, Rhinoviral Infections
- How many people
- 10,034 participants
- Where
- 1 siteUnited States
- Study dates
- 28 Jun 2023to 15 Jun 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: Adults age 18 years of age and older
Who may be able to join
- 18 years of age and older
Who cannot join
- Less than 18 years of age
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Digital Health Technologies for Infectious Disease Monitoring
This study will reach out to patients who have undergone diagnostic testing for the following respiratory illnesses from January 1st, 2018 to July 9th, 2023: COVID-19, Influenza, Rhinovirus, and Respiratory Syncytial Virus. This study aims to develop a forecasting model to predict infection onset prior to symptom onset using wearable device data and known symptom onset and test dates.
Read the detailed description
DUHS patients who have diagnostic testing for Influenza, COVID-19, Respiratory syncytial virus, and Rhinovirus testing within the past 5 years will be initially screened for an email address. Participants will learn about this study via email with a link to complete the survey. A Study ID will be generated for all individuals with an email.
Participants will be asked to complete an e-consent via a REDCap survey. If participants have questions, they are provided with study contact information via e-mail. Participants will complete the survey which will have questions on prior symptoms and device ownership (anticipated time to complete: 5 minutes). If the participant owns one of the following wearable devices (Fitbit, Garmin, or Apple Watch), they will be sent to a redirect URL to login into their device account (for Fitbit or Garmin) or be provided with instructions to export their Healthkit data and dump their data into a unique Strongbox link (for Apple Watch). If participants choose to contribute their wearable device data to the study and the data obtained pass through data quality thresholds, they will receive compensation. There is no compensation for survey completion. The investigators will ask participants if they wish to be re-contacted for future studies related to this project.
The investigators will collect endpoint data values from the wearable. These data will be used to estimate daily activity amounts and intensity (i.e., exercise and walking), standing, sleep amounts, sleep quality, heart rate variability, SpO2, respiratory rate, and heart rate. All of the wearable device data will be identified using a Study ID.
The investigators will use statistical and machine learning models to develop personalized "baseline" models of health and detect anomalies that can help in identifying COVID-19 infection. The investigators will validate and test the sensitivity and specificity of our mode for detecting respiratory infection vs. no infection against symptom surveys and diagnostic testing as ground truth. The model testing and validation will be done separately for each brand of device and will be further modified according to the type of respiratory infection.
- Conditions
- COVID-19 Respiratory Infection, Respiratory Syncytial Virus Infections, Rhinoviral Infections, Influenza Viral Infections
- Keywords
- Wearable Device, Smart Watch
- Medical subject headings
- Respiratory Syncytial Virus Infections
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Adults 18 years of age and up | The study will recruit any adult over the age of 18 years. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Develop a forecasting model to predict infection onset prior to symptom onset using the amount of time between known symptom onset and test dates
Known symptom onset and test dates will serve to validate the model
Measured: 18 Months
Secondary outcomes (6)
Determine if there are signal differences that can differentiate the type of respiratory infection (e.g., COVID-19 vs. Influenza)
Measured: 18 Months
Percentage of missingness in the wearable device data
Used to determine the performance of the forecasting model.
Measured: 18 Months
Determine the performance of the forecasting model on a new viral strain through transfer learning
Measured: 18 Months
Determine if there are physiological differences between initial infection and reinfection
Measured: 18 Months
Determine if there are physiological differences between varying respiratory infections over time
Measured: 18 Months
Determine the performance of the forecasting model based on the severity of symptoms
Measured: 18 Months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Nov 2020
- Study start28 Jun 2023
- Primary completion15 Jun 2024
- Study completion15 Jun 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for COVID-19 Respiratory InfectionStudies of the same condition, open and under way.
- More trials run by Duke UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
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
- 10,034 participants (actual)
Sponsor and investigators
- Lead sponsor
- Duke University
- Sponsor type
- University, hospital or other
- Collaborators
- Biomedical Advanced Research and Development Authority
- Responsible party
- Sponsor
- Investigators
- Chris Woods, Principal investigator, Duke UniversityJessilyn Dunn, Principal investigator, Duke UniversityRyan Shaw, Principal investigator, Duke University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04623047
- Sponsor's protocol ID
- PRO00106404
- Status last verified
- Jun 2024
- First submitted
- 9 Nov 2020
- Last updated
- 3 Jul 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 3 Jul 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Digital Health Technologies for Infectious Disease Monitoring
- ClinicalTrials.gov ID
- NCT04623047
- Acronym / sponsor ID
- PRO00106404
- Conditions
- COVID-19 Respiratory Infection, Respiratory Syncytial Virus Infections, Rhinoviral Infections, Influenza Viral Infections
- Keywords
- Wearable Device, Smart Watch
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 10,034 participants (actual)
- Lead sponsor
- Duke UniversityUniversity, hospital or other
- Collaborators
- Biomedical Advanced Research and Development Authority
- Study start
- 28 Jun 2023 (actual)
- Primary completion
- 15 Jun 2024 (actual)
- Study completion
- 15 Jun 2024 (actual)
- First posted
- 10 Nov 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study will reach out to patients who have undergone diagnostic testing for the following respiratory illnesses from January 1st, 2018 to July 9th, 2023: COVID-19, Influenza, Rhinovirus, and Respiratory Syncytial Virus. This study aims to develop a forecasting model to predict infection onset prior to symptom onset using wearable device data and known symptom onset and test dates.
Detailed description
DUHS patients who have diagnostic testing for Influenza, COVID-19, Respiratory syncytial virus, and Rhinovirus testing within the past 5 years will be initially screened for an email address. Participants will learn about this study via email with a link to complete the survey. A Study ID will be generated for all individuals with an email.
Participants will be asked to complete an e-consent via a REDCap survey. If participants have questions, they are provided with study contact information via e-mail. Participants will complete the survey which will have questions on prior symptoms and device ownership (anticipated time to complete: 5 minutes). If the participant owns one of the following wearable devices (Fitbit, Garmin, or Apple Watch), they will be sent to a redirect URL to login into their device account (for Fitbit or Garmin) or be provided with instructions to export their Healthkit data and dump their data into a unique Strongbox link (for Apple Watch). If participants choose to contribute their wearable device data to the study and the data obtained pass through data quality thresholds, they will receive compensation. There is no compensation for survey completion. The investigators will ask participants if they wish to be re-contacted for future studies related to this project.
The investigators will collect endpoint data values from the wearable. These data will be used to estimate daily activity amounts and intensity (i.e., exercise and walking), standing, sleep amounts, sleep quality, heart rate variability, SpO2, respiratory rate, and heart rate. All of the wearable device data will be identified using a Study ID.
The investigators will use statistical and machine learning models to develop personalized "baseline" models of health and detect anomalies that can help in identifying COVID-19 infection. The investigators will validate and test the sensitivity and specificity of our mode for detecting respiratory infection vs. no infection against symptom surveys and diagnostic testing as ground truth. The model testing and validation will be done separately for each brand of device and will be further modified according to the type of respiratory infection.
Study design
- Observational model
- Other
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Adults 18 years of age and up | – | –The study will recruit any adult over the age of 18 years. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Adults age 18 years of age and older
Key inclusion criteria (1 listed)
- 18 years of age and older
Key exclusion criteria (1 listed)
- Less than 18 years of age
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Develop a forecasting model to predict infection onset prior to symptom onset using the amount of time between known symptom onset and test dates
Time frame: 18 Months
Known symptom onset and test dates will serve to validate the model
6 secondary outcomes
Determine if there are signal differences that can differentiate the type of respiratory infection (e.g., COVID-19 vs. Influenza)
Time frame: 18 Months
Percentage of missingness in the wearable device data
Time frame: 18 Months
Determine the performance of the forecasting model on a new viral strain through transfer learning
Time frame: 18 Months
Determine if there are physiological differences between initial infection and reinfection
Time frame: 18 Months
Determine if there are physiological differences between varying respiratory infections over time
Time frame: 18 Months
Determine the performance of the forecasting model based on the severity of symptoms
Time frame: 18 Months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 3 Jul 2024.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Chris Woods principal investigator
Duke University
Jessilyn Dunn principal investigator
Duke University
Ryan Shaw principal investigator
Duke University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of COVID-19 Respiratory Infection and Respiratory Syncytial Virus Infections, run by Duke University 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 1 inclusion and 1 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 3 Jul 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?
Develop a forecasting model to predict infection onset prior to symptom onset using the amount of time between known symptom onset and test dates (time frame: 18 Months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 3 Jul 2024.