Spatial diffusion of COVID-19: an ESDA approach to the second wave in Germany

Abstract This study examines the spatial dynamics of COVID-19 pandemic severity across German counties during the second wave. Using an exploratory spatial data analysis (ESDA) framework, we analyse a composite Pandemic Severity Index (PSI) to identify how severe outcomes clustered and evolved over time. Local indicators of spatial association (LISA) and spatial lag models (SLM) are applied to detect hotspot persistence and quantify weekly spatial spill-overs. Results reveal that pandemic severity was not randomly distributed but formed stable regional clusters, with strong spatial coupling between neighbouring counties (average ρ ≈ 0.46). Spatial patterns are consistent with expansion- diffusion dynamics, concentrated in central and eastern Germany. The study highlights how regional spatial dependence and shared vulnerabilities shaped the evolution of pandemic severity during the second wave of COVID-19 in Germany.