Spatiotemporal Characterization of Overdose Mortality in Georgia, USA Using Spectral and Nonlinear Interaction Analysis, 2003-2021

Abstract

Drug overdose mortality in the United States exhibits strong geographic heterogeneity and complex temporal evolution, yet most spatiotemporal studies focus on trends and risks without explicitly characterizing the underlying dynamical structure of overdose trajectories. We develop a nonlinear spectral-spatiotemporal framework to analyze county-level overdose mortality in the state of Georgia from 2003 to 2021. Annual mortality rates are decomposed into low- and high-frequency components to distinguish long-term epidemic pressure from short-term variability, and nonlinear cross-frequency interaction is quantified using bispectral intensity. Counties are grouped into spectral phenotypes using unsupervised clustering, and single-breakpoint change-point models are used to identify regime shifts and quantify post-break acceleration across phenotypes. We find that overdose dynamics across Georgia are dominated by persistent low-frequency growth with limited independent short-term volatility. Nonlinear amplification is spatially concentrated and co-occurs with strong long-term epidemic pressure. Despite synchronous statewide breakpoints around 2014, post-break growth accelerates most sharply in counties exhibiting high low-frequency power and elevated nonlinear interaction. Together, these results provide a mechanistically interpretable framework for identifying dynamical risk phenotypes and structural transitions in spatial overdose epidemics.

Figures (8)

• Figure 1: Overview of the nonlinear spectral-spatial analysis pipeline.
• Figure 2: Spatial distribution of multiscale overdose dynamics across Georgia counties (2003–2021). The left panel displays low-frequency spectral power, reflecting persistent long-term growth in overdose mortality, while the right panel shows high-frequency power, capturing short-term fluctuations and episodic volatility.
• Figure 3: Spatial distribution of log of bispectral intensity in overdose mortality across Georgia counties (2003--2021). Higher values indicate stronger nonlinear coupling between long-term and short-term components.
• Figure 4: Spectral clustering of Georgia counties based on low-, mid-, and high-frequency spectral power and nonlinear (bispectral) intensity. Counties are grouped into four distinct spectral phenotypes representing qualitatively different overdose dynamics over the period 2003--2021.
• Figure 5: Representative overdose mortality trajectories (2003--2021) for one county from each spectral cluster. All panels share a common vertical scale to enable direct visual comparison of long-term growth patterns.