Particle emission concept and probabilistic consideration of the development of infections in systems
Dynamics from logarithm and exponent in the infection process, percolation effects
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Beschreibung
The book describes the possibility of making a probabilistic prognosis, which uses the mean n-day logarithm of case numbers in the past to determine an exponent for a probability density for a prognosis, as well as the particle emission concept, which is derived from contact and distribution rates that increase the exponent of the probable development to the extent that a group of people can be formed.
The contentTrends in the spread of infections, distribution and contact ratesAddition of the 4th parameter kurtosis to the density EqbPrediction using the density function and continuous adjustment of the parametersBasics for exponential propagation, the logarithm of historical dataDevelopments in the USAIncidence under probabilistic aspectsOn the percolation theory COVIDExamples of percolation effects
Thetarget groups
Management of health resources and services, virology, students, statisticians
The authorMarcus Hellwig is quality manager according to qualification by the German Society for Quality DGQ and author of reference books.
The book describes the possibility of making a probabilistic prognosis, which uses the mean n-day logarithm of case numbers in the past to determine an exponent for a probability density for a prognosis, as well as the particle emission concept, which is derived from contact and distribution rates that increase the exponent of the probable development to the extent that a group of people can be formed.
To create a probabilistic forecast Derivation of the particulate emission concept from contact and distribution rates Comprehensive consideration of the interrelationships
Autor*in
Marcus Hellwig
Themen in »Particle emission concept and probabilistic consideration of the development of infections in systems«
Spread of biological infections corona virus Distribution rate and contact rate Basis for a probabilistic forecast Doubts about statistical surveys The difference between influenza flu and COVID wave Analysis of density Eqb Addition of the parameter Kurtosis to the density Eqb4 Prediction using the density function Principles for exponential propagation Logarithm of historical data Hygiene consequences Handshake Breathing air (aerosols) Dynamic exponent