Real-time tracking of self-reported symptoms to predict potential COVID-19
Top Cited Papers
Open Access
- 11 May 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Nature Medicine
- Vol. 26 (7), 1037-1040
- https://doi.org/10.1038/s41591-020-0916-2
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.Funding Information
- Chronic Disease Research Foundation
- RCUK | Medical Research Council (AIMHY; MR/M016560/1, AIMHY; MR/M016560/1)
- DH | NIHR | Health Services Research Programme
- Alzheimer’s Society (AS-JF-17-011)
- Evergrande COVID-19 Response Fund Reward
- Wellcome Trust (WT203148/Z/16/Z, WT203148/Z/16/Z)
- Steele Foundation
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