Phylogenetic Insights into SARS-CoV-2 Introductions and Spread in Georgia

The spread of successive novel COVID-19 variants presented a challenge for outbreak surveillance, epidemiology, and emergency responses. Monitoring the emergence and spread of SARS-CoV-2 variants is essential to allocate limited public health resources and optimize control efforts. Global collaboration among the scientific community enabled large-scale viral surveillance and sequencing efforts. However, translating these vast datasets into actionable public health inferences requires rapid statistical methodologies, scalable workflows, and robust frameworks. In this study, we focused on the Delta epidemic wave in Georgia by applying a hybrid maximum likelihood (ML) and Bayesian phylodynamic approach. We characterized the Delta variant introduction to Georgia and its subsequent local spread. Our analysis of 9,783 Delta sequences collected between August 1, 2020 and January 25, 2022 detected at least 344 introductions into Georgia, resulting in 34 highly-supported local clusters. On average, clusters circulated for one month before the earliest detected sequence, highlighting critical delays in detection. While most clusters remained small, a few introduction events led to large, sustained outbreaks. We jointly inferred the statewide transmission network, estimated from all locally circulating clusters with a modified Bayesian discrete trait phylogeographic reconstruction of statewide health districts. We showed that South Central, Georgia was a major source of transmission, despite having smaller numbers of infected people, compared to major metropolitan areas. Our study addresses the urgent need for methodologies and data-driven recommendations for public health practice, particularly given large, dynamic, and integrated datasets. By identifying key geographic sources and sinks of transmission, our findings can guide resource allocation and prepare for future epidemics among high-risk populations. Additionally, by characterizing introduction events, local circulation, and detection lags, we highlight critical gaps in surveillance. These gaps can inform outbreak investigation and response, such as targeted contact tracing and testing.