Author: Drew, David A.; Nguyen, Long H.; Steves, Claire J.; Menni, Cristina; Freydin, Maxim; Varsavsky, Thomas; Sudre, Carole H.; Cardoso, M. Jorge; Ourselin, Sebastien; Wolf, Jonathan; Spector, Tim D.; Chan, Andrew T.
Title: Rapid implementation of mobile technology for real-time epidemiology of COVID-19 Cord-id: wfgmvy9i Document date: 2020_5_5
ID: wfgmvy9i
Snippet: The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garne
Document: The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic (COVID-19) presents challenges to the robust collection of population-scale data to address this global health crisis. We established the COronavirus Pandemic Epidemiology (COPE) consortium to bring together scientists with expertise in big data research and epidemiology to develop a COVID-19 Symptom Tracker mobile application that we launched in the UK on March 24, 2020 and the US on March 29, 2020 garnering more than 2.8 million users as of May 2, 2020. This mobile application offers data on risk factors, herald symptoms, clinical outcomes, and geographical hot spots. This initiative offers critical proof-of-concept for the repurposing of existing approaches to enable rapidly scalable epidemiologic data collection and analysis which is critical for a data-driven response to this public health challenge.
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