Spatio-temporal patterns of the SARS-CoV-2 epidemic in Germany

  • Results from an explorative study revealing spatio-temporal patterns of the SARS-CoV-2/ COVID-19 epidemic in Germany are presented. We dispense with contestable model assumptions and show the intrinsic spatio-temporal patterns of the epidemic dynamics. The analysis is based on COVID-19 incidence data, which are age-stratified and spatially resolved at the county level, provided by the Federal Government's Public Health Institute of Germany (RKI) for public use. Although the 400 county-related incidence time series shows enormous heterogeneity, both with respect to temporal features as well as spatial distributions, the counties' incidence curves organise into well-distinguished clusters that coincide with East and West Germany. The analysis is based on dimensionality reduction, multidimensional scaling, network analysis, and diversity measures. Dynamical changes are captured by means of difference-in-difference methods, which are related to fold changes of the effective reproduction numbers. The age-related dynamical patterns suggest a considerably stronger impact of children, adolescents and seniors on the epidemic activity than previously expected. Besides these concrete interpretations, the work mainly aims at providing an atlas for spatio-temporal patterns of the epidemic, which serves as a basis to be further explored with the expertise of different disciplines, particularly sociology and policy makers. The study should also be understood as a methodological contribution to getting a handle on the unusual complexity of the COVID-19 pandemic.

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Author:Hans H. DiebnerORCiDGND
Parent Title (English):Entropy
Place of publication:Basel
Document Type:Article
Date of Publication (online):2024/02/26
Date of first Publication:2023/07/29
Publishing Institution:Ruhr-Universität Bochum, Universitätsbibliothek
Tag:Open Access Fonds
COVID-19; SARS-CoV-2; cluster analysis; diversity; epidemic spatial heterogeneity; spatio-temporal patterns
Issue:8, Article 1137
First Page:1137-1
Last Page:1137-24
Article Processing Charge funded by the Deutsche Forschungsgemeinschaft (DFG) and the Open Access Publication Fund of Ruhr-Universität Bochum.
Institutes/Facilities:Abteilung für Medizinische Informatik, Biometrie und Epidemiologie
Dewey Decimal Classification:Technik, Medizin, angewandte Wissenschaften / Medizin, Gesundheit
open_access (DINI-Set):open_access
Licence (English):License LogoCreative Commons - CC BY 4.0 - Attribution 4.0 International