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Real-time tracking of self-reported symptoms to predict potential COVID-19.
Menni, Cristina; Valdes, Ana M; Freidin, Maxim B; Sudre, Carole H; Nguyen, Long H; Drew, David A; Ganesh, Sajaysurya; Varsavsky, Thomas; Cardoso, M Jorge; El-Sayed Moustafa, Julia S; Visconti, Alessia; Hysi, Pirro; Bowyer, Ruth C E; Mangino, Massimo; Falchi, Mario; Wolf, Jonathan; Ourselin, Sebastien; Chan, Andrew T; Steves, Claire J; Spector, Tim D.
  • Menni C; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK. cristina.menni@kcl.ac.uk.
  • Valdes AM; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Freidin MB; Academic Rheumatology, Clinical Sciences, Nottingham City Hospital, Nottingham, UK.
  • Sudre CH; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Nguyen LH; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Drew DA; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Ganesh S; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
  • Varsavsky T; Zoe Global, London, UK.
  • Cardoso MJ; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • El-Sayed Moustafa JS; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Visconti A; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Hysi P; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Bowyer RCE; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Mangino M; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Falchi M; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Wolf J; NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, UK.
  • Ourselin S; Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
  • Chan AT; Zoe Global, London, UK.
  • Steves CJ; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
  • Spector TD; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Nat Med ; 26(7): 1037-1040, 2020 07.
Article in English | MEDLINE | ID: covidwho-232776
ABSTRACT
A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who reported loss of smell and taste was higher in those with a positive test result (4,668 of 7,178 individuals; 65.03%) than in those with a negative test result (2,436 of 11,223 participants; 21.71%) (odds ratio = 6.74; 95% confidence interval = 6.31-7.21). A model combining symptoms to predict probable infection was applied to the data from all app users who reported symptoms (805,753) and predicted that 140,312 (17.42%) participants are likely to have COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Disease Notification / Self Report / Prodromal Symptoms / Mobile Applications / Smartphone Type of study: Diagnostic study / Observational study / Prognostic study Country/Region as subject: North America / Europa Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2020 Document Type: Article Affiliation country: S41591-020-0916-2

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Disease Notification / Self Report / Prodromal Symptoms / Mobile Applications / Smartphone Type of study: Diagnostic study / Observational study / Prognostic study Country/Region as subject: North America / Europa Language: English Journal: Nat Med Journal subject: Molecular Biology / Medicine Year: 2020 Document Type: Article Affiliation country: S41591-020-0916-2