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

TY - JOUR

T1 - Rapid implementation of mobile technology for real-time epidemiology of COVID-19

AU - COPE Consortium

AU - Drew, David A

AU - Nguyen, Long H

AU - Steves, Claire J

AU - Menni, Cristina

AU - Freydin, Maxim

AU - Varsavsky, Thomas

AU - Sudre, Carole H

AU - Cardoso, M Jorge

AU - Ourselin, Sebastien

AU - Wolf, Jonathan

AU - Spector, Tim D

AU - Chan, Andrew T

N1 - Funding Information: Use of the COVID-19 app in cohorts and informed consent as described was approved by the Partners Human Research Committee (Protocol 2020P000909) and is registered on ClinicalTrials.gov as NCT04331509. We acknowledge J. Capdevila Pujol of Zoe Global Ltd. for his contributions to this work. Zoe Global Ltd. provided in kind support for all aspects of building, running, and supporting the tracking app and service to all users worldwide. C.J.S., C.M., M.F., T.V., C.H.S., M.J.C., S.O., and T.D.S. were supported by the Wellcome Trust and EPSRC (WT212904/Z/18/Z, WT203148/Z/16/Z, and WT213038/Z/18/Z), the NIHR GSTT/KCL Biomedical Research Centre, MRC/BHF (MR/M016560/1), the NIHR, and the Alzheimer's Society (AS-JF-17-011). A.T.C. is the Stuart and Suzanne Steele MGH Research Scholar and Stand Up to Cancer scientist. L.H.N., D.A.D., and A.T.C. were supported by the Massachusetts Consortium on Pathogen Readiness (MassCPR), M. Schwartz, and L. Schwartz. Author Publisher Copyright: © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works

PY - 2020/6/19

Y1 - 2020/6/19

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85086031247&partnerID=8YFLogxK

U2 - 10.1126/science.abc0473

DO - 10.1126/science.abc0473

M3 - Article

C2 - 32371477

SN - 0036-8075

VL - 368

SP - 1362

EP - 1367

JO - Science

JF - Science

IS - 6497

ER -