Preprint Article Version 1 This version is not peer-reviewed

Gaussian Doubling Times and Reproduction Factors of the COVID-19 Pandemic Disease

Version 1 : Received: 12 May 2020 / Approved: 13 May 2020 / Online: 13 May 2020 (03:40:22 CEST)

How to cite: Kröger, M.; Schlickeiser, R. Gaussian Doubling Times and Reproduction Factors of the COVID-19 Pandemic Disease. Preprints 2020, 2020050219 (doi: 10.20944/preprints202005.0219.v1). Kröger, M.; Schlickeiser, R. Gaussian Doubling Times and Reproduction Factors of the COVID-19 Pandemic Disease. Preprints 2020, 2020050219 (doi: 10.20944/preprints202005.0219.v1).

Abstract

The Gauss model for the time evolution of the first corona pandemic wave rendered useful in the estimation of peak times, amount of required equipment, and the forecasting of fade out times. At the same time it is probably the simplest analytically tractable model that allows to quantitatively forecast the time evolution of infections and fatalities during a pandemic wave. In light of the various descriptors such as doubling times and reproduction factors currently in use to judge about lock-downs and other measures that aim to prevent spreading of the virus, we hereby provide both exact, and simple approximate relationships between the two relevant parameters of the Gauss model (peak time and width), and the transient behavior of two versions of doubling times, and three variants of reproduction factors including basic reproduction numbers.

Supplementary and Associated Material

http://www.complexfluids.ethz.ch/corona: COVID-19 real time statistics & extrapolation using the Gauss model (GM)

Subject Areas

coronavirus; statistical analysis; extrapolation; parameter estimation; pandemic spreading

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