Author: Janik Schuttler; Reinhard Schlickeiser; Frank Schlickeiser; Martin Kroger
Title: Covid-19 predictions using a Gauss model, based on data from April 2 Document date: 2020_4_11
ID: 14x9luqu_19
Snippet: Sigmoidal functions are popular to model saturation processes such as cellular growth [20, 21] or enzyme (Michaelis-Menten) kinetics. Numerous sigmoidal functions exist and they have been used in many variations to predict infectious diseases [8] and have even been linked directly to models such as the SIR model [17] . Not surprisingly, sigmoidal models are frequently used in times of coronavirus [7, 15, 18] , most often using a (generalized) log.....
Document: Sigmoidal functions are popular to model saturation processes such as cellular growth [20, 21] or enzyme (Michaelis-Menten) kinetics. Numerous sigmoidal functions exist and they have been used in many variations to predict infectious diseases [8] and have even been linked directly to models such as the SIR model [17] . Not surprisingly, sigmoidal models are frequently used in times of coronavirus [7, 15, 18] , most often using a (generalized) logistic function (Richard's curve). One model particularly similar to our GM [12] also uses the Gaussian integral as sigmoidal function with similar parameters. However, the study only applies to the US, for which we . 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.
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