Stochastic modeling of the evolution of highly contagious virus transmission in crowded places
Valery Fedosov- Alina Fedossova
- Oscar Buitrago-Suescún
Published 2020-11-03
Keywords
- virus transmission,
- contagion,
- social distancing,
- crowd,
- algorithm
- stochastic behavior,
- mathematical modeling,
- health authority,
- biosecurity protocols,
- numerical experiments,
- SARS-COv-2,
- COVID 19 ...More
How to Cite
Copyright (c) 2020 Revista UIS Ingenierías
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
Abstract
A mathematical model is proposed for stochastic estimation of the number of the SARS-COv-2 virus infected person in places where there is a high concentration of population, such as shopping centers or other closed spaces. The aim is to obtain a mathematical model of virus propagation in closed spaces calculating the number of infected depending on compliance or violation of safe distances and compliance with protection standards, as well as a heuristic algorithm for their solution. Mathematical modeling was used to research the virus transmission situation and to develop a heuristic algorithm for the solution of the obtained mathematical model. The programming, the numerical experiments and the figures were constrained in MATLAB. The numerical experiments obtained for some cases show the dependence between the number of new infected with non-compliance of the recommendations for social distancing and the use of personal protection elements. The model is open to additions and improvements and may be of interest to support the decisions making process of the health and administrative authorities. The algorithm solves the proposed mathematical model to track virus transmission when the recommended safe and secure distances are not fulfilled. The application of the algorithm allows to propose controls in complex and unpredictable situations of epidemic development in population concentrations, so it can be used to improve the quality of proactive medical measures and other related decisions.
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References
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