Real-time tracking of self-reported symptoms to predict potential COVID-19
- PMID: 32393804
- PMCID: PMC7751267
- DOI: 10.1038/s41591-020-0916-2
Real-time tracking of self-reported symptoms to predict potential COVID-19
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.
Conflict of interest statement
Competing interests
T.D.S. and A.M.V. are consultants to Zoe Global. S.G. and J.W. are employees of Zoe Global.
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Comment in
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Is a COVID-19 prediction model based on symptom tracking through an app applicable in primary care?Fam Pract. 2020 Nov 28;37(6):866-867. doi: 10.1093/fampra/cmaa069. Fam Pract. 2020. PMID: 32719842 Free PMC article. No abstract available.
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