Real-time tracking of self-reported symptoms to predict potential COVID-19

Nat Med. 2020 Jul;26(7):1037-1040. doi: 10.1038/s41591-020-0916-2. Epub 2020 May 11.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Betacoronavirus / physiology
  • Computer Systems
  • Coronavirus Infections / diagnosis*
  • Coronavirus Infections / epidemiology
  • Coronavirus Infections / pathology
  • Cough / diagnosis
  • Cough / epidemiology
  • Disease Notification / methods*
  • Disease Notification / standards
  • Dyspnea / diagnosis
  • Dyspnea / epidemiology
  • Fatigue / diagnosis
  • Fatigue / epidemiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Mobile Applications* / standards
  • Models, Biological
  • Olfaction Disorders / diagnosis
  • Olfaction Disorders / epidemiology
  • Pandemics
  • Pneumonia, Viral / diagnosis*
  • Pneumonia, Viral / epidemiology
  • Pneumonia, Viral / pathology
  • Prodromal Symptoms*
  • Prognosis
  • Self Report*
  • Severity of Illness Index
  • Smartphone*
  • Taste Disorders / diagnosis
  • Taste Disorders / epidemiology
  • United Kingdom / epidemiology
  • United States / epidemiology

Supplementary concepts

  • COVID-19
  • severe acute respiratory syndrome coronavirus 2