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App-Based Tracking of Self-Reported COVID-19 Symptoms: Analysis of Questionnaire Data
Martin Zens1, Arne Brammertz2, Juliane Herpich1
1Department of Medicine, Kliniken Ostallgaeu-Kaufbeuren, Fuessen, Germany.
Journal of Medical Internet Research
|August 14, 2020
Summary
COVID-19 symptom tracking via an app identified key predictors like loss of smell and nausea. Diabetes and heart disease were significant risk factors for severe COVID-19 illness.
Area of Science:
- Epidemiology
- Infectious Diseases
- Public Health
Background:
- COVID-19 presents with diverse clinical symptoms, necessitating early identification methods.
- Understanding symptom distribution aids in early detection of infected individuals.
Purpose of the Study:
- To determine the distribution of COVID-19 symptoms.
- To identify potential unreported symptoms using an app-based self-reporting tool.
Main Methods:
- Developed an app-based daily self-reporting tool for symptom tracking.
- Collected demographic and medical history data from 22,327 participants.
- Analyzed symptom data from 11,829 participants, including those tested for SARS-CoV-2.
Main Results:
- Positive COVID-19 cases reported an average of 5.63 symptoms.
- Diabetes (OR 8.95) and chronic heart disease (OR 2.85) were significant risk factors.
- Top predictors for infection included chills, fever, loss of smell, nausea/vomiting, and shortness of breath.
Conclusions:
- Self-reported symptom tracking can identify novel symptoms and assess predictive values.
- Loss of smell and taste should be considered cardinal symptoms of COVID-19.
- Diabetes is a risk factor for a more severe COVID-19 disease course.
