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

被引：239

作者：

Drew, David A. ^{[1
,2
]}

Nguyen, Long H. ^{[1
,2
]}

Steves, Claire J. ^{[3
,4
]}

Menni, Cristina ^{[3
]}

Freydin, Maxim ^{[3
]}

Varsavsky, Thomas ^{[5
]}

Sudre, Carole H. ^{[5
]}

Cardoso, M. Jorge ^{[5
]}

Ourselin, Sebastien ^{[5
]}

Wolf, Jonathan ^{[6
]}

Spector, Tim D. ^{[3
,6
]}

Chan, Andrew T. ^{[1
,2
,7
]}

机构：

[1] Massachusetts Gen Hosp, Clin & Translat Epidemiol Unit, 55 Fruit St, Boston, MA 02114 USA

[2] Harvard Med Sch, 55 Fruit St, Boston, MA 02114 USA

[3] Kings Coll London, Dept Twin Res & Genet Epidemiol, Westminster Bridge Rd, London SE1 7EH, England

[4] Guys & St Thomas NHS Fdn Trust, Dept Ageing & Hlth, Lambeth Palace Rd, London SE1 7EH, England

[5] Kings Coll London, Sch Biomed Engn & Imaging Sci, 1 Lambeth Palace Rd, London SE1 7EU, England

[6] Zoe Global Ltd, 164 Westminster Bridge Rd, London SE1 7RW, England

[7] Harvard TH Chan Sch Publ Hlth, Dept Immunol & Infect Dis, 665 Huntington Ave, Boston, MA 02114 USA

来源：

SCIENCE | 2020年 / 368卷 / 6497期

基金：

英国工程与自然科学研究理事会; 英国惠康基金; 英国医学研究理事会;

关键词：

CLINICAL CHARACTERISTICS;

D O I：

10.1126/science.abc0473

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页码：1362 / +

页数：16

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