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

PLoS One. 2021 Jun 30;16(6):e0253566. doi: 10.1371/journal.pone.0253566. eCollection 2021.

Abstract

Background: Monitoring 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.

Methods: COVID 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.

Results: Since 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.

Discussion: The 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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • COVID-19 / epidemiology*
  • Child
  • Child, Preschool
  • Cohort Studies
  • Female
  • Health Behavior*
  • Humans
  • Infant
  • Infant, Newborn
  • Male
  • Middle Aged
  • Mobile Applications*
  • Physical Distancing
  • Public Health Surveillance / methods*
  • Radar
  • Self Report
  • Young Adult

Grants and funding

Funding for the project was obtained from ZonMW (the Netherlands Organization of Health Research and Development, grant numbers: 10430042010016, 10430022010001 and 10430032010011). The company, ORTEC, provided support in the form of the salary of author MeB. The funder provided support in the form of salaries for authors WJD and NS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.