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|a dc
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|a Allen, William E.
|e author
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|a Massachusetts Institute of Technology. Department of Biological Engineering
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|a Harvard University-
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|a McGovern Institute for Brain Research at MIT
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|a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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|a Altae-Tran, Han
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|a Briggs, James
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|a Jin, Xin
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|a McGee, Glen
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|a Shi, Andy
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|a Raghavan, Rumya
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|a Kamariza, Mireille
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|a Nova, Nicole
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|a Pereta, Albert
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|a Danford, Chris
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|a Kamel, Amine
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|a Gothe, Patrik
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|a Milam, Evrhet
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|a Aurambault, Jean
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|a Primke, Thorben
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|a Li, Weijie
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|a Inkenbrandt, Josh
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|a Huynh, Tuan
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|a Chen, Evan
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|a Lee, Christina
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|a Croatto, Michael
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|a Bentley, Helen
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|a Lu, Wendy
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|a Murray, Robert
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|a Travassos, Mark
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|a Coull, Brent A.
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|a Openshaw, John
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|a Greene, Casey S.
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|a Shalem, Ophir
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|a King, Gary
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|a Probasco, Ryan
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|a Cheng, David R.
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|a Silbermann, Ben
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|a Zhang, Feng
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|a Lin, Xihong
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|a Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing
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|b Springer Science and Business Media LLC,
|c 2021-01-04T22:14:22Z.
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|z Get fulltext
|u https://hdl.handle.net/1721.1/128952
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|a Despite the widespread implementation of public health measures, coronavirus disease 2019 (COVID-19) continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behaviour and demographics. Here, we report results from over 500,000 users in the United States from 2 April 2020 to 12 May 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation; show a variety of exposure, occupational and demographic risk factors for COVID-19 beyond symptoms; reveal factors for which users have been SARS-CoV-2 PCR tested; and highlight the temporal dynamics of symptoms and self-isolation behaviour. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure and behavioural self-reported data to fight the COVID-19 pandemic.
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|a en
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|a Article
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|t Nature Human Behaviour
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