Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app.
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| Title: | Geo-social gradients in predicted COVID-19 prevalence in Great Britain: results from 1 960 242 users of the COVID-19 Symptoms Study app. |
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| Authors: | Bowyer RCE; Twin Research, King's College London, London, UK., Varsavsky T; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK., Thompson EJ; Twin Research, King's College London, London, UK., Sudre CH; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.; MRC Unit for Lifelong Health and Ageing, University College London, London, UK., Murray BAK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK., Freidin MB; Twin Research, King's College London, London, UK., Yarand D; Twin Research, King's College London, London, UK., Ganesh S; Zoe Global Limited, London, UK., Capdevila J; Zoe Global Limited, London, UK., Bakker E; Zoe Global Limited, London, UK., Cardoso MJ; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK., Davies R; Zoe Global Limited, London, UK., Wolf J; Zoe Global Limited, London, UK., Spector TD; Twin Research, King's College London, London, UK., Ourselin S; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK., Steves CJ; Twin Research, King's College London, London, UK., Menni C; Twin Research, King's College London, London, UK cristina.menni@kcl.ac.uk. |
| Source: | Thorax [Thorax] 2021 Jul; Vol. 76 (7), pp. 723-725. Date of Electronic Publication: 2020 Dec 29. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: British Medical Assn Country of Publication: England NLM ID: 0417353 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1468-3296 (Electronic) Linking ISSN: 00406376 NLM ISO Abbreviation: Thorax Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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