RSI model: COVID-19 in Germany Alternating quarantine episodes and normal episodes

  1. Carolin Knoch
  2. Timo Hartmann
  3. Alan Wildblood

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Abstract

This paper was developed in the Civil Systems Engineering Department at the Technical University of Berlin. The background is the spread of COVID-19 pandemic in Germany. Our current situation is a threat from the COVID-19 virus without vaccine and medication. Germany has increased its intensive capacities, intensified research in its analyzes and research projects and is currently testing the influence of various measures on the rate of expansion.

The goal now is to find a strategy that slows the spread so that medical capacities are not overloaded. The approach is to alternate between quarantine and normal episodes and the result is an oscillation in the number of cases between two limits.

The mathematical model is an SRI model that can be used to calculate the development of the case numbers. All uncertain parameters are varied at significant intervals. Influence parameters and control parameters were defined. By adjusting the length of the episode to match the speed of spread of the virus, the gap can be bridged until a vaccine has been developed or sufficient immunity is available in the population. By observing the capacity limits in connection with the number of cases, the need for a new quarantine episode and the possibility of initiating a normal episode can be predetermined. This does not exceed the capacity limit.

In quarantine, contagion within households is limited by the size of the household; only system-critical professions continue to work in public. All others must remain in the homeschooling / home office. In the normal episode, everyone can work, go to school, have social contacts. A solution could be found in all parameter combinations. The ratio of the normal episode duration / quarantine episode lies between 0.3 and 0.95 in the examination area.

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    SciScore for 10.1101/2020.05.01.20075754: (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

    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.

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    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

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    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.05.01.20075754v1 on medRxiv