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Smell and taste symptom-based predictive model for COVID-19 diagnosis
Lauren T Roland1, Jose G Gurrola1, Patricia A Loftus1
1Department of Otolaryngology-Head and Neck Surgery, University of California, San Francisco, San Francisco, CA.
International Forum of Allergy & Rhinology
|May 5, 2020
Summary
Changes in smell or taste, along with fever, can help predict a positive coronavirus 2019 (COVID-19) test. This symptom combination accurately identifies 75% of COVID-19 cases, aiding in early detection.
Area of Science:
- Epidemiology
- Infectious Diseases
- Public Health
Background:
- Coronavirus 2019 (COVID-19) symptoms overlap with influenza, complicating diagnosis.
- Limited data exists on specific symptoms predicting COVID-19 test positivity.
Purpose of the Study:
- To identify key symptoms for predicting COVID-19 test positivity.
- To develop a predictive model for COVID-19 diagnosis.
Main Methods:
- An anonymous electronic survey collected data on 10 symptoms, demographics, and comorbidities.
- Stepwise logistic regression identified predictors of COVID-19 positivity.
- Receiver operating characteristic (ROC) curve analysis assessed classifier performance.
Main Results:
- Smell/taste change, fever, and body ache were associated with COVID-19 positivity.
- Shortness of breath and sore throat were linked to negative test results.
- A 5-symptom model achieved 82% accuracy; a 2-symptom model (smell/taste change + fever) achieved 75% accuracy.
Conclusions:
- Smell or taste alteration is a significant predictor of COVID-19 positivity.
- A classifier combining smell/taste change and fever predicts 75% of COVID-19 results.
- Further research with larger cohorts is needed to refine predictive models.
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