Covid-19 predictions using a Gauss model, based on data from April 2

Janik Schuttler; Reinhard Schlickeiser; Frank Schlickeiser; Martin Kroger

Using the fitted polynomial coefficients we compute the three parameters of the GM, i.e. maximum height, time of maximum height and curve width, for each country. For mathematical details, please refer to the appendix. To demonstrate the universal Gaussian nature of the daily fatalities over time d, we display them in Fig. 3(a,b) , normalized so that all curves have unit width, maximum and time of maximum. The same plots for the cumulative fatalities D are shown in Fig. 3(c,d) . Daily infections i, daily fatalities d, cumulative infections I and cumulative fatalities D, all fit neatly onto the unit GM curve or its cumulative function, plotted in gray in the back for reference. China, which is the only country to provide data from its first pandemic wave for times greater than 0.6 (in normalized units), fits to the GM well over the entire significant course of infections and fatalities. This sparks the hope that the used GM will have predictive power for the remaining countries also after the maximum. The fits already provide sufficient evidence that the part prior to the maximum is captured well by the GM. The resulting GM parameters are listed and plotted in Fig. 4 . For most countries the GM width is within 10 and 15 days, roughly half of all countries have passed their peak of daily fatalities already and the peak is roughly below 20 fatalities per day and per million people. . CC-BY-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.