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Title: The COronavirus Pandemic Epidemiology (COPE) Consortium: A Call to Action.

Authors: Chan, Andrew T; Drew, David A; Nguyen, Long H; Joshi, Amit D; Ma, Wenjie; Guo, Chuan-Guo; Lo, Chun-Han; Mehta, Raaj S; Kwon, Sohee; Sikavi, Daniel R; Magicheva-Gupta, Marina V; Fatehi, Zahra S; Flynn, Jacqueline J; Leonardo, Brianna M; Albert, Christine M; Andreotti, Gabriella; Beane-Freeman, Laura E; Balasubramanian, Bijal A; Brownstein, John S; Bruinsma, Fiona; Cowan, Annie N; Deka, Anusila; Ernst, Michael E; Figueiredo, Jane C; Franks, Paul W; Gardner, Christopher D; Ghobrial, Irene M; Haiman, Christopher A; Hall, Janet E; Deming-Halverson, Sandra L; Kirpach, Brenda; Lacey Jr, James V; Marchand, Loïc Le; Marinac, Catherine R; Martinez, Maria Elena; Milne, Roger L; Murray, Anne M; Nash, Denis; Palmer, Julie R; Patel, Alpa V; Rosenberg, Lynn; Sandler, Dale P; Sharma, Shreela V; Schurman, Shepherd H; Wilkens, Lynne R; Chavarro, Jorge E; Eliassen, A Heather; Hart, Jaime E; Kang, Jae Hee; Koenen, Karestan C; Kubzansky, Laura D; Mucci, Lorelei A; Ourselin, Sebastien; Rich-Edwards, Janet W; Song, Mingyang; Stampfer, Meir J; Steves, Claire J; Willett, Walter C; Wolf, Jonathan; Spector, Tim; COPE Consortium

Published In Cancer Epidemiol Biomarkers Prev, (2020 Jul)

Abstract: The rapid pace of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) pandemic presents challenges to the real-time collection of population-scale data to inform near-term public health needs as well as future investigations. We established the COronavirus Pandemic Epidemiology (COPE) consortium to address this unprecedented crisis on behalf of the epidemiology research community. As a central component of this initiative, we have developed a COVID Symptom Study (previously known as the COVID Symptom Tracker) mobile application as a common data collection tool for epidemiologic cohort studies with active study participants. This mobile application collects information on risk factors, daily symptoms, and outcomes through a user-friendly interface that minimizes participant burden. Combined with our efforts within the general population, data collected from nearly 3 million participants in the United States and United Kingdom are being used to address critical needs in the emergency response, including identifying potential hot spots of disease and clinically actionable risk factors. The linkage of symptom data collected in the app with information and biospecimens already collected in epidemiology cohorts will position us to address key questions related to diet, lifestyle, environmental, and socioeconomic factors on susceptibility to COVID-19, clinical outcomes related to infection, and long-term physical, mental health, and financial sequalae. We call upon additional epidemiology cohorts to join this collective effort to strengthen our impact on the current health crisis and generate a new model for a collaborative and nimble research infrastructure that will lead to more rapid translation of our work for the betterment of public health.

PubMed ID: 32371551 Exiting the NIEHS site

MeSH Terms: Betacoronavirus*; COVID-19; Coronavirus Infections/diagnosis; Coronavirus Infections/epidemiology*; Data Collection/methods*; Humans; Models, Biological; Pandemics*; Pneumonia, Viral/diagnosis; Pneumonia, Viral/epidemiology*; Public Health; SARS-CoV-2; Smartphone; Software*; United Kingdom/epidemiology; United States/epidemiology

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