A benchmark of online COVID-19 symptom checkers

  1. Nicolas Munsch
  2. Alistair Martin
  3. Stefanie Gruarin
  4. Jama Nateqi
  5. Isselmou Abdarahmane
  6. Rafael Weingartner-Ortner
  7. Bernhard Knapp
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Abstract

Background

A large number of online COVID-19 symptom checkers and chatbots have been developed but anecdotal evidence suggests that their conclusions are highly variable. To our knowledge, no study has evaluated the accuracy of COVID-19 symptom checkers in a statistically rigorous manner.

Methods

In this paper, we evaluate 10 different COVID-19 symptom checkers screening 50 COVID-19 case reports alongside 410 non-COVID-19 control cases.

Results

We find that the number of correctly assessed cases varies considerably between different symptom checkers, with Symptoma (F1=0.92, MCC=0.85) showing the overall best performance followed by Infermedica (F1=0.80, MCC=0.61).

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