Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany.
COVID-19
Germany
Mesoscale outbreak dynamics
SIQRD model
Journal
Biomechanics and modeling in mechanobiology
ISSN: 1617-7940
Titre abrégé: Biomech Model Mechanobiol
Pays: Germany
ID NLM: 101135325
Informations de publication
Date de publication:
Feb 2022
Feb 2022
Historique:
received:
23
01
2021
accepted:
15
09
2021
pubmed:
7
10
2021
medline:
10
2
2022
entrez:
6
10
2021
Statut:
ppublish
Résumé
The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.
Identifiants
pubmed: 34613527
doi: 10.1007/s10237-021-01520-x
pii: 10.1007/s10237-021-01520-x
pmc: PMC8493548
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
119-133Informations de copyright
© 2021. The Author(s).
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