Digital acoustic surveillance for early detection of respiratory disease outbreaks in Spain: a protocol for an observational study
| Autor: | Dominique Hélène Doré, Juan C. Gabaldon-Figueira, Virginia Orrillo, Carlos Chaccour, Lai Yu Tsang, Simon Lapierre, Javier Bartolomé, Alejandro Fernández-Montero, Isabel Blavia, Juliane Chaccour, Nita Umashankar, Joe Brew |
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| Rok vydání: | 2021 |
| Předmět: |
Canada
medicine.medical_specialty Population Context (language use) Disease Outbreaks respiratory infections 03 medical and health sciences 0302 clinical medicine Artificial Intelligence Pandemic Epidemiology Humans Medicine 030212 general & internal medicine education Respiratory Medicine Pandemics education.field_of_study Disease surveillance SARS-CoV-2 business.industry COVID-19 Acoustics General Medicine medicine.disease Focus group Observational Studies as Topic Spain epidemiology Observational study Medical emergency business 030217 neurology & neurosurgery |
| Zdroj: | BMJ Open BMJ Open, Vol 11, Iss 7 (2021) |
| ISSN: | 2044-6055 |
| DOI: | 10.1136/bmjopen-2021-051278 |
| Popis: | IntroductionCough 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 analysisParticipants 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 disseminationEthics 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 numberNCT04762693. |
| Databáze: | OpenAIRE |
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