Spatio-Temporal Patterns of the SARS-CoV-2 Epidemic in Germany

Area of Science:

• Epidemiology
• Public Health
• Data Science

Background:

• The COVID-19 pandemic presented unprecedented challenges in understanding disease spread.
• Spatio-temporal analysis is crucial for effective epidemic control and resource allocation.

Purpose of the Study:

• To identify and characterize intrinsic spatio-temporal patterns of the SARS-CoV-2/COVID-19 epidemic in Germany.
• To provide an atlas of epidemic dynamics, free from contestable model assumptions.
• To offer a methodological contribution to analyzing complex pandemic data.

Main Methods:

• Utilized age-stratified, county-level COVID-19 incidence data from the Robert Koch Institute (RKI).
• Employed dimensionality reduction, multidimensional scaling, network analysis, and diversity measures.
• Applied difference-in-difference methods to capture dynamical changes and effective reproduction numbers.

Main Results:

• Identified distinct clusters of COVID-19 incidence patterns correlating with East and West Germany.
• Revealed significant heterogeneity across approximately 400 county-level incidence time series.
• Indicated a stronger-than-expected impact of children, adolescents, and seniors on epidemic activity.

Conclusions:

• Spatio-temporal clustering provides insights into Germany's COVID-19 epidemic structure.
• Age-stratified analysis reveals key demographic drivers of transmission.
• The findings serve as a foundation for interdisciplinary research and policy-making.