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Rapid implementation of mobile technology for real-time epidemiology of COVID-19.

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Title: Rapid implementation of mobile technology for real-time epidemiology of COVID-19.
Authors: 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.
Source: Science (pre-March 2025). 6/19/2020, Vol. 368 Issue 6497, p1362-1367. 6p. 2 Diagrams, 2 Graphs.
Subjects: SARS-CoV-2, COVID-19, Epidemiology, Symptoms, Big data
Abstract: The rapid pace of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 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 unite scientists with expertise in big data research and epidemiology to develop the COVID Symptom Study, previously known as the COVID Symptom Tracker, mobile application. This application—which offers data on risk factors, predictive symptoms, clinical outcomes, and geographical hotspots—was launched in the United Kingdom on 24 March 2020 and the United States on 29 March 2020 and has garnered more than 2.8 million users as of 2 May 2020. Our initiative offers a 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. [ABSTRACT FROM AUTHOR]
Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="AR" term="%22Drew%2C+David+A%2E%22">Drew, David A.</searchLink><br /><searchLink fieldCode="AR" term="%22Nguyen%2C+Long+H%2E%22">Nguyen, Long H.</searchLink><br /><searchLink fieldCode="AR" term="%22Steves%2C+Claire+J%2E%22">Steves, Claire J.</searchLink><br /><searchLink fieldCode="AR" term="%22Menni%2C+Cristina%22">Menni, Cristina</searchLink><br /><searchLink fieldCode="AR" term="%22Freydin%2C+Maxim%22">Freydin, Maxim</searchLink><br /><searchLink fieldCode="AR" term="%22Varsavsky%2C+Thomas%22">Varsavsky, Thomas</searchLink><br /><searchLink fieldCode="AR" term="%22Sudre%2C+Carole+H%2E%22">Sudre, Carole H.</searchLink><br /><searchLink fieldCode="AR" term="%22Cardoso%2C+M%2E+Jorge%22">Cardoso, M. Jorge</searchLink><br /><searchLink fieldCode="AR" term="%22Ourselin%2C+Sebastien%22">Ourselin, Sebastien</searchLink><br /><searchLink fieldCode="AR" term="%22Wolf%2C+Jonathan%22">Wolf, Jonathan</searchLink><br /><searchLink fieldCode="AR" term="%22Spector%2C+Tim+D%2E%22">Spector, Tim D.</searchLink><br /><searchLink fieldCode="AR" term="%22Chan%2C+Andrew+T%2E%22">Chan, Andrew T.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Science+%28pre-March+2025%29%22">Science (pre-March 2025)</searchLink>. 6/19/2020, Vol. 368 Issue 6497, p1362-1367. 6p. 2 Diagrams, 2 Graphs.
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  Data: The rapid pace of the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 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 unite scientists with expertise in big data research and epidemiology to develop the COVID Symptom Study, previously known as the COVID Symptom Tracker, mobile application. This application—which offers data on risk factors, predictive symptoms, clinical outcomes, and geographical hotspots—was launched in the United Kingdom on 24 March 2020 and the United States on 29 March 2020 and has garnered more than 2.8 million users as of 2 May 2020. Our initiative offers a 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. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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              Text: 6/19/2020
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