Six scenarios of non-medical interventions in the SARS-CoV-2 epidemic
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Abstract
We investigate six scenarios spanning main parts of the decision space of non-medical interventions against the CoV-2 epidemic in Germany. Based on the notion of interventions-lifting we classify and evaluate the scenarios by five attributes (indicators): amount of interventions-lifting, death numbers, Public Health Care capacity, population immunity, peak dates of infections. For quantitative reasoning we use a simulated modified SEIR-model calibrated with actual data. We identify margins for intervention-liftings wrt. 13.05.2020 and discuss the relation to the effective reproduction number with a 6d-generation time. We show that, in order to constrain death numbers comparable to a strong Influenza epidemic, there is only a small corridor of 16% of possible liftings, with an additional 4% margin contributed by automated contact tracing. We show also that there is a much broader corridor of 50%+18%, though not overloading critical Public Health Care capacity, implying high death numbers.
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SciScore for 10.1101/2020.05.25.20112532: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
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 …
SciScore for 10.1101/2020.05.25.20112532: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
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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