Abstract

For Germany, it is predicted that the first wave of the corona pandemic disease reaches its maximum of new infections on 11 April 2020 − 3.4 + 5.4 days with 90% confidence. With a delay of about 7 days the maximum demand on breathing machines in hospitals occurs on 18 April 2020 − 3.4 + 5.4 days. The first pandemic wave ends in Germany end of May 2020. The predictions are based on the assumption of a Gaussian time evolution well justified by the central limit theorem of statistics. The width and the maximum time and thus the duration of this Gaussian distribution are determined from a statistical χ 2 -fit to the observed doubling times before 28 March 2020.

Highlights

  • In these days there is a very high interest in the societal, economical and political world to understand the time evolution of the first wave of infections of the population by the current Sars-Cov-2(corona) virus

  • The best justification for the Gaussian, or normal, distribution for the virus time evolution is given by the central limit theorem of statistics [1]

  • Numerical simulations and the empirical data of earlier epidemics [10] indicate that the time evolution of epidemic waves is characterized by an early exponential rise until a pronounced maximum is reached followed by a rapid decrease

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Summary

Introduction

In these days there is a very high interest in the societal, economical and political world to understand the time evolution of the first wave of infections of the population by the current Sars-Cov-2. The most important issues are the total duration and the peak time of the infection evolution as well as the maximum number of daily infections It would be most helpful for many people to have a reproducible, crude, but reliable estimate when this pandemic wave is over. The best justification for the Gaussian, or normal, distribution for the virus time evolution is given by the central limit theorem of statistics [1]. To the best of our knowledge this manuscript is the first application of the Gaussian model to the COVID-19 pandemic in Germany It differs from the earlier work [2,3] by proposing the use of monitored doubling times to infer the total duration and the peak time of the first wave of infections. We base our parameter estimates on publicly available information, especially by the podcast [10] and the recent sophisticated modeling study for Germany [9]

Gaussian Model
Doubling Time
Statistical Fit
Total Number of Infections
Manageable Infections
Duration of the First Wave
Findings
Final Important Remark
Full Text
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