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

Willian J Van Dijk,Jiska J Aardoom,Tobias N Bonten,Nicholas H Saadah,Jessica Kiefte-De Jong,Mattijs E Numans,Niels H Chavannes,Frits Rosendaal,Michelle Brust,Rutger A Middelburg,Saskia Le Cessie,Leo G Visser,Menno Brandjes,Simone Lolli

doi:10.1371/journal.pone.0253566

Willian J Van Dijk, Jiska J Aardoom + Show 12 more

Open Access

https://doi.org/10.1371/journal.pone.0253566

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Abstract

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. 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. 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. 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.

Highlights

The world is in the throes of the coronavirus-disease-2019 (COVID-19) pandemic with more than 100 million cases and over 2 million confirmed deaths worldwide as of December 2020 [1]
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

Summary

Introduction

The world is in the throes of the coronavirus-disease-2019 (COVID-19) pandemic with more than 100 million cases and over 2 million confirmed deaths worldwide as of December 2020 [1]. In the Netherlands, the first case of COVID-19 was diagnosed in February 2020 and since over one million cases and 17,500 deaths have been confirmed [2]. An important limitation of the TTI strategy is transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by COVID-19 carriers without symptoms. Given their lack of symptoms, they may not be tested and remain unidentified by the TTI process despite being a possible source of viral transmission [6]. The COVID Radar smartphone app, active in the Netherlands, allows users to selfreport symptoms, social distancing behaviors, and COVID-19 status daily. The objective of this study is to describe the validation of the COVID Radar

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Results

Conclusion