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Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution

Kühn, Martin Joachim and Abele, Daniel and Mitra, Tanmay and Koslow, Wadim and Abedi, Majid and Rack, Kathrin and Siggel, Martin and Khailaie, Sahamoddin and Klitz, Margrit and Binder, Sebastian and Spataro, Luca and Gilg, Jonas and Kleinert, Jan and Häberle, Matthias and Plötzke, Lena and Spinner, Christoph D. and Stecher, Melanie and Zhu, Xiao Xiang and Basermann, Achim and Meyer-Hermann, Michael (2021) Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution. Mathematical Biosciences, 339, p. 108648. Elsevier. doi: 10.1016/j.mbs.2021.108648. ISSN 0025-5564.

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Official URL: https://www.sciencedirect.com/science/article/pii/S0025556421000845

Abstract

Non-pharmaceutical interventions (NPIs) are important to mitigate the spread of infectious diseases as long as no vaccination or outstanding medical treatments are available. We assess the effectiveness of the sets of non-pharmaceutical interventions that were in place during the course of the Coronavirus disease 2019 (Covid-19) pandemic in Germany. Our results are based on hybrid models, combining SIR-type models on local scales with spatial resolution. In order to account for the age-dependence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we include realistic prepandemic and recently recorded contact patterns between age groups. The implementation of non-pharmaceutical interventions will occur on changed contact patterns, improved isolation, or reduced infectiousness when, e.g., wearing masks. In order to account for spatial heterogeneity, we use a graph approach and we include high-quality information on commuting activities combined with traveling information from social networks. The remaining uncertainty will be accounted for by a large number of randomized simulation runs. Based on the derived factors for the effectiveness of different non-pharmaceutical interventions over the past months, we provide different forecast scenarios for the upcoming time.

Item URL in elib:https://elib.dlr.de/146707/
Document Type:Article
Title:Assessment of effective mitigation and prediction of the spread of SARS-CoV-2 in Germany using demographic information and spatial resolution
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Kühn, Martin JoachimMartin.Kuehn (at) dlr.dehttps://orcid.org/0000-0002-0906-6984
Abele, DanielDaniel.Abele (at) dlr.deUNSPECIFIED
Mitra, TanmayDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, GermanyUNSPECIFIED
Koslow, WadimWadim.Koslow (at) dlr.deUNSPECIFIED
Abedi, MajidDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, GermanyUNSPECIFIED
Rack, KathrinKathrin.Rack (at) dlr.dehttps://orcid.org/0000-0002-5794-5705
Siggel, Martinmartin.siggel (at) dlr.dehttps://orcid.org/0000-0002-3952-4659
Khailaie, SahamoddinDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, GermanyUNSPECIFIED
Klitz, MargritMargrit.Klitz (at) dlr.dehttps://orcid.org/0000-0003-3657-4180
Binder, SebastianDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germanyhttps://orcid.org/0000-0003-1169-1786
Spataro, LucaLuca.Spataro (at) dlr.deUNSPECIFIED
Gilg, JonasJonas.Gilg (at) dlr.deUNSPECIFIED
Kleinert, JanJan.Kleinert (at) dlr.dehttps://orcid.org/0000-0002-2709-214X
Häberle, MatthiasMatthias.Haeberle (at) dlr.dehttps://orcid.org/0000-0001-9550-5252
Plötzke, LenaLena.Ploetzke (at) dlr.deUNSPECIFIED
Spinner, Christoph D.Technical University of Munich, School of Medicine, University Hospital rechts der Isar, Department of Internal Medicine II, Munich, GermanyUNSPECIFIED
Stecher, MelanieUniversity Hospital of Cologne, Department I for Internal Medicine, University of Cologne; German Center for Infection Research (DZIF), Cologne, GermanyUNSPECIFIED
Zhu, Xiao Xiangxiao.zhu (at) dlr.dehttps://orcid.org/0000-0001-5530-3613
Basermann, AchimAchim.Basermann (at) dlr.dehttps://orcid.org/0000-0003-3637-3231
Meyer-Hermann, MichaelDepartment of Systems Immunology and Braunschweig Integrated Centre of Systems Biology (BRICS), Helmholtz Centre for Infection Research, Braunschweig, Germanyhttps://orcid.org/0000-0002-4300-2474
Date:July 2021
Journal or Publication Title:Mathematical Biosciences
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:339
DOI :10.1016/j.mbs.2021.108648
Page Range:p. 108648
Publisher:Elsevier
ISSN:0025-5564
Status:Published
Keywords:SARS-CoV-2 Covid-19 Coronavirus disease Mitigation Non-pharmaceutical interventions Forecast
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Space System Technology
DLR - Research area:Raumfahrt
DLR - Program:R SY - Space System Technology
DLR - Research theme (Project):R - Tasks SISTEC, R - Artificial Intelligence
Location: Köln-Porz , Oberpfaffenhofen
Institutes and Institutions:Institute for Software Technology > High-Performance Computing
Institute for Software Technology > Software for Space Systems and Interactive Visualisation
Remote Sensing Technology Institute > EO Data Science
Deposited By: Kühn, Dr. Martin Joachim
Deposited On:03 Dec 2021 13:03
Last Modified:07 Dec 2021 12:59

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