Author: Reinhard Schlickeiser; Frank Schlickeiser
Title: A Gaussian model for the time development of the Sars-Cov-2 corona pandemic disease. Predictions for Germany made on March 30, 2020 Document date: 2020_4_2
ID: 0sny9dit_2
Snippet: The best justification for the Gaussian or normal distribution for the virus time evolution is given by the central limit theorem of statistics 1 . The central limit theorem states that in situations, when many n 1 independent random variables are added, their properly normalized sum tends toward a normal or Gaussian distribution function of the form (1) even if the original variables themselves are not normally distributed. The spread of the vir.....
Document: The best justification for the Gaussian or normal distribution for the virus time evolution is given by the central limit theorem of statistics 1 . The central limit theorem states that in situations, when many n 1 independent random variables are added, their properly normalized sum tends toward a normal or Gaussian distribution function of the form (1) even if the original variables themselves are not normally distributed. The spread of the virus infection of populations with high number of persons certainly is such a random process to which the central limit theorem ia applicable. Each person in a given population has a probability distribution (normalized to unity) as a function of time of being infected: it is a very noncontinuous distribution being 1 at the day of infection and 0 on all other days. If one adds up these discrete distributions of persons living in villages and districts of towns of typical size of about 1000 persons one obtains quasi-continous probability distributions for be- * rsch@tp4.rub.de, schlickeiser@gmail.com ing infected which certainly will be different in hotspots of the disease and isolated rural areas. If we then add up a large number of these village probability distributions for all of Germany we obtain the daily infection rate distribution which according to the central limit is close to a Gaussian distribution.
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