Rapid Optimization of COVID-19 Testing for People Affected by Diabetes

Background: The purpose of this study was to rapidly scale and optimize COVID-19 testing for adults and children at high risk due to metabolic diseases such as diabetes, obesity, or elevated diabetes risk. Georgia, a state with one of the highest diabetes rates in the U.S., was experiencing rapidly increasing COVID-19 cases, morbidity, and mortality, yet lacked sufficient testing opportunities for underserved high-risk populations. This study aimed to address access gaps, improve resource allocation, and enhance testing and education strategies to support individuals at the time of and following their test results.

Materials/Methods: The Georgia Center for Diabetes Translation Research leveraged its interdisciplinary expertise and partnerships across community, academic, government, and healthcare sectors to implement the Rapid Optimization of COVID-19 Testing for People Affected by Diabetes program. The study adapted and iteratively refined a testing and education strategy delivered through Federally Qualified Health Centers (FQHCs) and community testing centers using a “test your bubble” approach that encouraged household testing. Geospatial analyses identified testing deserts within counties with high concentrations of at-risk populations. Community and clinic stakeholders were engaged to identify barriers, facilitators, and user-preferred testing strategies. Predictive models were developed to guide real-time decisions about whom, where, and when to test. The intervention was deployed and evaluated through rapid-cycle testing in a pre-post effectiveness-implementation hybrid study. Sustainability was measured through continuous quality improvement activities.

Outcome/Impact: This study strengthened COVID-19 testing infrastructure for high-risk, underserved communities in Georgia and informed scalable strategies for future serological testing and vaccination efforts. The program’s reach, effectiveness, adoption, implementation, and maintenance were assessed using the RE-AIM framework. The outcomes were expected to improve testing accessibility, inform public health strategies, and enhance pandemic preparedness in similarly underserved regions.