Using publicly available data to identify priority communities for a SARS-CoV-2 testing intervention in a southern...

Area of Science:

• Public Health
• Epidemiology
• Health Disparities

Background:

• The U.S. Southeast faces a significant burden of SARS-CoV-2 infections and COVID-19.
• Rural Alabama was targeted for a precision population health intervention to enhance SARS-CoV-2 testing.
• The intervention period spanned October 2020 to March 2021.

Approach:

• Utilized public data and community engagement to select counties for intervention.
• Modeled county-level SARS-CoV-2 positivity rates using risk, severity, and mitigation covariates.
• Presented descriptive epidemiologic data to advisory boards for county prioritization.

Key Points:

• In October 2020, no factors correlated with SARS-CoV-2 positivity.
• By March 2021, premature death rates, percent Black residents, preventable hospitalizations, and smoking rates were associated with positivity.
• Counties were ranked by positivity, fatality, case rates, and testing sites.

Conclusions:

• Modeling SARS-CoV-2 proved challenging due to its dynamic nature.
• Epidemiological data facilitated community stakeholder engagement for testing implementation.
• Community involvement in data interpretation is crucial for addressing local diseases.