PLoS ONE (Jan 2021)

COVID RADAR app: Description and validation of population surveillance of symptoms and behavior in relation to COVID-19.

  • Willian J van Dijk,
  • Nicholas H Saadah,
  • Mattijs E Numans,
  • Jiska J Aardoom,
  • Tobias N Bonten,
  • Menno Brandjes,
  • Michelle Brust,
  • Saskia le Cessie,
  • Niels H Chavannes,
  • Rutger A Middelburg,
  • Frits Rosendaal,
  • Leo G Visser,
  • Jessica Kiefte-de Jong

DOI
https://doi.org/10.1371/journal.pone.0253566
Journal volume & issue
Vol. 16, no. 6
p. e0253566

Abstract

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BackgroundMonitoring of symptoms and behavior may enable prediction of emerging COVID-19 hotspots. The COVID Radar smartphone app, active in the Netherlands, allows users to self-report symptoms, social distancing behaviors, and COVID-19 status daily. The objective of this study is to describe the validation of the COVID Radar.MethodsCOVID Radar users are asked to complete a daily questionnaire consisting of 20 questions assessing their symptoms, social distancing behavior, and COVID-19 status. We describe the internal and external validation of symptoms, behavior, and both user-reported COVID-19 status and state-reported COVID-19 case numbers.ResultsSince April 2nd, 2020, over 6 million observations from over 250,000 users have been collected using the COVID Radar app. Almost 2,000 users reported having tested positive for SARS-CoV-2. Amongst users testing positive for SARS-CoV-2, the proportion of observations reporting symptoms was higher than that of the cohort as a whole in the week prior to a positive SARS-CoV-2 test. Likewise, users who tested positive for SARS-CoV-2 showed above average risk social-distancing behavior. Per-capita user-reported SARS-CoV-2 positive tests closely matched government-reported per-capita case counts in provinces with high user engagement.DiscussionThe COVID Radar app allows voluntarily self-reporting of COVID-19 related symptoms and social distancing behaviors. Symptoms and risk behavior increase prior to a positive SARS-CoV-2 test, and user-reported case counts match closely with nationally-reported case counts in regions with high user engagement. These results suggest the COVID Radar may be a valid instrument for future surveillance and potential predictive analytics to identify emerging hotspots.