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Syga, S.* ; David-Rus, D.* ; Schälte, Y. ; Hatzikirou, H.* ; Deutsch, A.*

Inferring the effect of interventions on COVID-19 transmission networks.

Sci. Rep. 11:21913 (2021)
Publ. Version/Full Text Research data DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Countries around the world implement nonpharmaceutical interventions (NPIs) to mitigate the spread of COVID-19. Design of efficient NPIs requires identification of the structure of the disease transmission network. We here identify the key parameters of the COVID-19 transmission network for time periods before, during, and after the application of strict NPIs for the first wave of COVID-19 infections in Germany combining Bayesian parameter inference with an agent-based epidemiological model. We assume a Watts–Strogatz small-world network which allows to distinguish contacts within clustered cliques and unclustered, random contacts in the population, which have been shown to be crucial in sustaining the epidemic. In contrast to other works, which use coarse-grained network structures from anonymized data, like cell phone data, we consider the contacts of individual agents explicitly. We show that NPIs drastically reduced random contacts in the transmission network, increased network clustering, and resulted in a previously unappreciated transition from an exponential to a constant regime of new cases. In this regime, the disease spreads like a wave with a finite wave speed that depends on the number of contacts in a nonlinear fashion, which we can predict by mean field theory.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Small-world; Sars-cov-2; Complex; Infection; Model
ISSN (print) / ISBN 2045-2322
e-ISSN 2045-2322
Journal Scientific Reports
Quellenangaben Volume: 11, Issue: 1, Pages: , Article Number: 21913 Supplement: ,
Publisher Nature Publishing Group
Publishing Place London
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Grants
German Federal Ministry of Education and Research (FitMultiCell)
Bundesministeriums fur Bildung, und Forschung (BMBF)
Volkswagen Foundation within the Life? program
European Social Fund (ESF)