Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany
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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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SciScore for 10.1101/2021.01.21.21250215: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Using the next generation matrix approach (Diekmann et al., 2010), the reproduction number for the SEIRD-model can be calculated yielding The system of non-linear ordinary equations (1) - (5) is numerically solved using an explicit Runge-Kutta method of order 5(4), derived by Dormand et al., 1980 and implemented by SciPy 1.0 Contributors et al., 2020.
SciPysuggested: (SciPy, RRID:SCR_008058)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An …SciScore for 10.1101/2021.01.21.21250215: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources Using the next generation matrix approach (Diekmann et al., 2010), the reproduction number for the SEIRD-model can be calculated yielding The system of non-linear ordinary equations (1) - (5) is numerically solved using an explicit Runge-Kutta method of order 5(4), derived by Dormand et al., 1980 and implemented by SciPy 1.0 Contributors et al., 2020.
SciPysuggested: (SciPy, RRID:SCR_008058)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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