Digital Acoustic Surveillance for Early Detection of Respiratory Disease Outbreaks
NCT ID: NCT04762693
Last Updated: 2022-07-20
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
930 participants
OBSERVATIONAL
2020-11-11
2022-05-24
Brief Summary
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Detailed Description
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The app in question, Hyfe cough tracker, runs in the background of smartphones, and records short snippets (\<0.5 seconds) of explosive, putative cough sounds. These are then classified as cough or non-cough, using a convolutional neural network (CNN) model, and matched to GPS and time data collected by the smartphone.
The night-time cough of participants will be monitored for a 30-day period, and their clinical records will be reviewed regularly, specifically looking for diagnoses of cough-producing diseases, and with special emphasis on COVID-19.
Cough data will be used to create a heatmap of cough density and geographic distribution. Aggregated cough registries will be used to calculate the coughs per person-hour registered in the cohort. These data will be used to carry out an ARIMA analysis on three parallel time series at the community level: The incidence of respiratory disease in the monitored cohort, in the entire study area (including the Universidad de Navarra, and the neighbouring Cendea de Cizur), and the cough frequency per monitored hours.
Changes in cough frequency will also be compared to other environmental variables such as temperature and pollution level registered in the study area.
Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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Cough monitoring
All enrolled participants will be asked to install the acoustic surveillance software in their smartphones and use it to record night-time coughs for a minimum 30-day period.
Hyfe cough tracker
A mobile app that runs in the background of smartphones and detects putative cough sounds.
Interventions
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Hyfe cough tracker
A mobile app that runs in the background of smartphones and detects putative cough sounds.
Eligibility Criteria
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Inclusion Criteria
* Own and regularly use a smartphone able to run the cough-tracking system,
* Be willing to install and regularly use it,
* Be current residents of Navarra, and
* Have an active relationship with the university (having interest in the study, or being a student or worker, be a patient with a cough-related diagnosis at the Clínica Universidad de Navarra, or Cizur's health centre).
Exclusion Criteria
* Inability to grant access to medical records.
13 Years
99 Years
ALL
Yes
Sponsors
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Centre de Recherche du Centre Hospitalier de l'Université de Montréal
OTHER
Clinica Universidad de Navarra, Universidad de Navarra
OTHER
Responsible Party
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Principal Investigators
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Carlos Chaccour
Role: PRINCIPAL_INVESTIGATOR
Clínica Universidad de Navarra
Locations
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Universidad de Navarra
Pamplona, Navarre, Spain
Countries
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References
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Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 Feb 15;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24.
Kim GU, Kim MJ, Ra SH, Lee J, Bae S, Jung J, Kim SH. Clinical characteristics of asymptomatic and symptomatic patients with mild COVID-19. Clin Microbiol Infect. 2020 Jul;26(7):948.e1-948.e3. doi: 10.1016/j.cmi.2020.04.040. Epub 2020 May 1.
Peeling RW, Wedderburn CJ, Garcia PJ, Boeras D, Fongwen N, Nkengasong J, Sall A, Tanuri A, Heymann DL. Serology testing in the COVID-19 pandemic response. Lancet Infect Dis. 2020 Sep;20(9):e245-e249. doi: 10.1016/S1473-3099(20)30517-X. Epub 2020 Jul 17.
Chowdhury R, Luhar S, Khan N, Choudhury SR, Matin I, Franco OH. Long-term strategies to control COVID-19 in low and middle-income countries: an options overview of community-based, non-pharmacological interventions. Eur J Epidemiol. 2020 Aug;35(8):743-748. doi: 10.1007/s10654-020-00660-1. Epub 2020 Jul 13.
Rasheed J, Jamil A, Hameed AA, Aftab U, Aftab J, Shah SA, Draheim D. A survey on artificial intelligence approaches in supporting frontline workers and decision makers for the COVID-19 pandemic. Chaos Solitons Fractals. 2020 Dec;141:110337. doi: 10.1016/j.chaos.2020.110337. Epub 2020 Oct 10.
Porter P, Abeyratne U, Swarnkar V, Tan J, Ng TW, Brisbane JM, Speldewinde D, Choveaux J, Sharan R, Kosasih K, Della P. A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centred analytic system for the identification of common respiratory disorders in children. Respir Res. 2019 Jun 6;20(1):81. doi: 10.1186/s12931-019-1046-6.
Sharan RV, Abeyratne UR, Swarnkar VR, Claxton S, Hukins C, Porter P. Predicting spirometry readings using cough sound features and regression. Physiol Meas. 2018 Sep 5;39(9):095001. doi: 10.1088/1361-6579/aad948.
Santillana M, Nguyen AT, Louie T, Zink A, Gray J, Sung I, Brownstein JS. Cloud-based Electronic Health Records for Real-time, Region-specific Influenza Surveillance. Sci Rep. 2016 May 11;6:25732. doi: 10.1038/srep25732.
Mukundarajan H, Hol FJH, Castillo EA, Newby C, Prakash M. Using mobile phones as acoustic sensors for high-throughput mosquito surveillance. Elife. 2017 Oct 31;6:e27854. doi: 10.7554/eLife.27854.
Naseem M, Akhund R, Arshad H, Ibrahim MT. Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review. J Prim Care Community Health. 2020 Jan-Dec;11:2150132720963634. doi: 10.1177/2150132720963634.
Liss DT, Serrano E, Wakeman J, Nowicki C, Buchanan DR, Cesan A, Brown T. "The Doctor Needs to Know": Acceptability of Smartphone Location Tracking for Care Coordination. JMIR Mhealth Uhealth. 2018 May 4;6(5):e112. doi: 10.2196/mhealth.9726.
Galvosas M, Gabaldon-Figueira JC, Keen EM, Orrillo V, Blavia I, Chaccour J, Small PM, Gimenez G, Rudd M, Grandjean Lapierre S, Chaccour C. Performance evaluation of the smartphone-based AI cough monitoring app - Hyfe Cough Tracker against solicited respiratory sounds. F1000Res. 2023 Jun 9;11:730. doi: 10.12688/f1000research.122597.2. eCollection 2022.
Gabaldon-Figueira JC, Brew J, Dore DH, Umashankar N, Chaccour J, Orrillo V, Tsang LY, Blavia I, Fernandez-Montero A, Bartolome J, Grandjean Lapierre S, Chaccour C. Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study. BMJ Open. 2021 Jul 2;11(7):e051278. doi: 10.1136/bmjopen-2021-051278.
Other Identifiers
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DASRD
Identifier Type: -
Identifier Source: org_study_id
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