Predictors of COVID-19 From a Statewide Digital Symptom and Risk Assessment Tool: Cross-Sectional Study

Area of Science:

• Public Health
• Health Informatics
• Epidemiology

Background:

• The COVID-19 pandemic highlighted challenges in tracking symptoms for disease mitigation in public spaces like schools and workplaces.
• Technology implementation, including symptom and risk assessment tools, offered solutions to manage pandemic repercussions and facilitate a return to normalcy.

Purpose of the Study:

• To explore the use of a COVID-19 symptom and risk assessment tool (Healthcheck) to mitigate disease exposure in public settings.
• To assess the correlation between user-reported symptoms and exposure via a mobile health app and confirmed COVID-19 cases in Alabama.

Main Methods:

• A cross-sectional study evaluated the relationship between confirmed COVID-19 cases (Alabama Department of Public Health data) and self-reported symptoms/exposure via the Healthcheck mobile app.
• Multiple linear regression analyzed the association between self-reported health data and confirmed COVID-19 diagnoses across the state population.

Main Results:

• Regression analysis indicated that self-reported symptoms via Healthcheck significantly impacted the number of confirmed COVID-19 cases.
• Specific symptoms like nausea/vomiting and high-risk reports correlated with increased daily cases, while sore throat reports correlated with decreased cases.

Conclusions:

• The Healthcheck platform enabled remote population tracking for COVID-19, aiding symptom tracking and risk assessment for public space entry.
• The established link between app-based symptom reporting and population-level cases suggests potential for such tools in mitigating community and individual disease spread.