Probabilistic Model of Interaction of Necessary and Sufficient Conditions for Mass Morbidity of the Population ....

Probabilistic Model of Interaction of Necessary and Sufficient Conditions for Mass Morbidity of the Population ....

Probabilistic Model of Interaction of Necessary and Sufficient Conditions for Mass Morbidity of the Population, Taking into Account the Scale-Population Factor Materials

A.A. Barzov, doctor of technical sciences, professor, leading researcher of the Center for hydrophysical research of faculty of physics, Moscow State University named after M.V. Lomonosov; Moscow
A.I. Denchik, candidate of technical sciences, professor, Mechanical Engineering and Standardization department of Pavlodar State University named after S. Toraigyrov; Republic of Kazakhstan, Pavlodar
V.M. Korneeva, doctor of technical sciences, associate professor, professor of the department «Metrology and interchangeability» of Bauman Moscow State Technical University, president of the Qualimetry branch of the Academy for Quality Problems; Moscow
e-mail: v_korneeva@list.ru
S.S. Korneev, candidate of technical sciences, associate professor, associate professor of the department «Rocket and space technologies engineering» of Bauman Moscow State Technical University; Moscow
It is proposed to use the phenomenology of the well-known «scale strength factor» to construct a hardware platform for probabilistic modeling of the interaction kinetics of necessary and sufficient conditions for the occurrence of epidemics or pandemics. Exponential-plastic models have been obtained that reflect the characteristic features of these mass-population phenomena, which provide the possibility of probabilistic forecasting of various scenarios of their course. Examples of calculations based on the proposed probabilistic model are given and their correspondence to real statistical data on the development of morbidity in different countries is shown.
Keywords: mass morbidity, probabilistic modeling, necessary and sufficient conditions, scale factor.
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DOI: 10.34214/2312-5209-2020-27-3-19-26

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