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Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany.
Schüler, Lennart; Calabrese, Justin M; Attinger, Sabine.
  • Schüler L; Institute of Earth and Environmental Sciences, University Potsdam, Potsdam, Germany.
  • Calabrese JM; Dept. of Computational Hydrosystems, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany.
  • Attinger S; Center for Advanced Systems Understanding (CASUS), Görlitz, Germany.
PLoS One ; 16(8): e0254660, 2021.
Article in English | MEDLINE | ID: covidwho-1362084
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ABSTRACT
The SARS-CoV-2 virus has spread around the world with over 100 million infections to date, and currently many countries are fighting the second wave of infections. With neither sufficient vaccination capacity nor effective medication, non-pharmaceutical interventions (NPIs) remain the measure of choice. However, NPIs place a great burden on society, the mental health of individuals, and economics. Therefore the cost/benefit ratio must be carefully balanced and a target-oriented small-scale implementation of these NPIs could help achieve this balance. To this end, we introduce a modified SEIRD-class compartment model and parametrize it locally for all 412 districts of Germany. The NPIs are modeled at district level by time varying contact rates. This high spatial resolution makes it possible to apply geostatistical methods to analyse the spatial patterns of the pandemic in Germany and to compare the results of different spatial resolutions. We find that the modified SEIRD model can successfully be fitted to the COVID-19 cases in German districts, states, and also nationwide. We propose the correlation length as a further measure, besides the weekly incidence rates, to describe the current situation of the epidemic.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Disease Control / Pandemics / COVID-19 Type of study: Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0254660

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Communicable Disease Control / Pandemics / COVID-19 Type of study: Observational study Topics: Vaccines Limits: Humans Country/Region as subject: Europa Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2021 Document Type: Article Affiliation country: Journal.pone.0254660