Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study
Introduction Cough is a common symptom of COVID-19 and other respiratory illnesses. However, objectively measuring its frequency and evolution is hindered by the lack of reliable and scalable monitoring systems. This can be overcome by newly developed artificial intelligence models that exploit the...
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doaj-78bcc1a8fc48478e9a7cf932ec481d202021-10-06T18:00:04ZengBMJ Publishing GroupBMJ Open2044-60552021-07-0111710.1136/bmjopen-2021-051278Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational studySimon Grandjean Lapierre0Joe Brew1Juan Carlos Gabaldon-Figueira2Dominique Hélène Doré3Nita Umashankar4Juliane Chaccour5Virginia Orrillo6Lai Yu Tsang7Isabel Blavia8Alejandro Fernández-Montero9Javier Bartolomé10C Chaccour11Immunopathology Axis, Research Center of the University of Montreal Hospital Center, Montréal, Québec, CanadaResearch and Development Department, Hyfe, Wilmington, Delaware, USAInfectious Diseases Area, University of Navarra Clinic, Pamplona, SpainImmunopathology Axis, Research Center of the University of Montreal Hospital Center, Montréal, Québec, CanadaFowler College of Business, San Diego State University, San Diego, California, USAInfectious Diseases Area, University of Navarra Clinic, Pamplona, SpainSchool of Pharmacy and Nutrition, University of Navarra, Pamplona, SpainGlobal Health Institute, Stony Brook University, Stony Brook, New York, USASchool of Pharmacy and Nutrition, University of Navarra, Pamplona, SpainDepartment of Occupational Medicine - COVID-19 area, University of Navarra Clinic, Pamplona, SpainPrimary Healthcare, Navarre Health Service-Osasunbidea, Zizur Mayor, SpainInfectious Diseases Area, University of Navarra Clinic, Pamplona, SpainIntroduction Cough is a common symptom of COVID-19 and other respiratory illnesses. However, objectively measuring its frequency and evolution is hindered by the lack of reliable and scalable monitoring systems. This can be overcome by newly developed artificial intelligence models that exploit the portability of smartphones. In the context of the ongoing COVID-19 pandemic, cough detection for respiratory disease syndromic surveillance represents a simple means for early outbreak detection and disease surveillance. In this protocol, we evaluate the ability of population-based digital cough surveillance to predict the incidence of respiratory diseases at population level in Navarra, Spain, while assessing individual determinants of uptake of these platforms.Methods and analysis Participants in the Cendea de Cizur, Zizur Mayor or attending the local University of Navarra (Pamplona) will be invited to monitor their night-time cough using the smartphone app Hyfe Cough Tracker. Detected coughs will be aggregated in time and space. Incidence of COVID-19 and other diagnosed respiratory diseases within the participants cohort, and the study area and population will be collected from local health facilities and used to carry out an autoregressive moving average analysis on those independent time series. In a mixed-methods design, we will explore barriers and facilitators of continuous digital cough monitoring by evaluating participation patterns and sociodemographic characteristics. Participants will fill an acceptability questionnaire and a subgroup will participate in focus group discussions.Ethics and dissemination Ethics approval was obtained from the ethics committee of the Centre Hospitalier de l’Université de Montréal, Canada and the Medical Research Ethics Committee of Navarre, Spain. Preliminary findings will be shared with civil and health authorities and reported to individual participants. Results will be submitted for publication in peer-reviewed scientific journals and international conferences.Trial registration number NCT04762693.https://bmjopen.bmj.com/content/11/7/e051278.full |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Simon Grandjean Lapierre Joe Brew Juan Carlos Gabaldon-Figueira Dominique Hélène Doré Nita Umashankar Juliane Chaccour Virginia Orrillo Lai Yu Tsang Isabel Blavia Alejandro Fernández-Montero Javier Bartolomé C Chaccour |
spellingShingle |
Simon Grandjean Lapierre Joe Brew Juan Carlos Gabaldon-Figueira Dominique Hélène Doré Nita Umashankar Juliane Chaccour Virginia Orrillo Lai Yu Tsang Isabel Blavia Alejandro Fernández-Montero Javier Bartolomé C Chaccour Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study BMJ Open |
author_facet |
Simon Grandjean Lapierre Joe Brew Juan Carlos Gabaldon-Figueira Dominique Hélène Doré Nita Umashankar Juliane Chaccour Virginia Orrillo Lai Yu Tsang Isabel Blavia Alejandro Fernández-Montero Javier Bartolomé C Chaccour |
author_sort |
Simon Grandjean Lapierre |
title |
Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study |
title_short |
Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study |
title_full |
Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study |
title_fullStr |
Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study |
title_full_unstemmed |
Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study |
title_sort |
digital acoustic surveillance for early detection of respiratory disease outbreaks in spain: a protocol for an observational study |
publisher |
BMJ Publishing Group |
series |
BMJ Open |
issn |
2044-6055 |
publishDate |
2021-07-01 |
description |
Introduction Cough is a common symptom of COVID-19 and other respiratory illnesses. However, objectively measuring its frequency and evolution is hindered by the lack of reliable and scalable monitoring systems. This can be overcome by newly developed artificial intelligence models that exploit the portability of smartphones. In the context of the ongoing COVID-19 pandemic, cough detection for respiratory disease syndromic surveillance represents a simple means for early outbreak detection and disease surveillance. In this protocol, we evaluate the ability of population-based digital cough surveillance to predict the incidence of respiratory diseases at population level in Navarra, Spain, while assessing individual determinants of uptake of these platforms.Methods and analysis Participants in the Cendea de Cizur, Zizur Mayor or attending the local University of Navarra (Pamplona) will be invited to monitor their night-time cough using the smartphone app Hyfe Cough Tracker. Detected coughs will be aggregated in time and space. Incidence of COVID-19 and other diagnosed respiratory diseases within the participants cohort, and the study area and population will be collected from local health facilities and used to carry out an autoregressive moving average analysis on those independent time series. In a mixed-methods design, we will explore barriers and facilitators of continuous digital cough monitoring by evaluating participation patterns and sociodemographic characteristics. Participants will fill an acceptability questionnaire and a subgroup will participate in focus group discussions.Ethics and dissemination Ethics approval was obtained from the ethics committee of the Centre Hospitalier de l’Université de Montréal, Canada and the Medical Research Ethics Committee of Navarre, Spain. Preliminary findings will be shared with civil and health authorities and reported to individual participants. Results will be submitted for publication in peer-reviewed scientific journals and international conferences.Trial registration number NCT04762693. |
url |
https://bmjopen.bmj.com/content/11/7/e051278.full |
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