Mathematical Modelling of Spread COVID-19 Epidemic for Preventive Measures to Protect Life and Health of Elderly

IF 0.2 Q4 MATHEMATICS, APPLIED

Bulletin of the South Ural State University Series-Mathematical Modelling Programming & Computer Software Pub Date : 2021-01-01 DOI:10.14529/mmp210307

Y. Bubeev, B. Vladimirskiy, I. Ushakov, V. Usov, A. Bogomolov

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引用次数: 0

Abstract

Quantitative approaches based on mathematical modelling are used to justify a set of measures aimed at justifying a set of preventive measures to protect the life and health of older people in the context of COVID-19 pandemic. Analysis of the state of development of actuarial mathematical models of mortality in the COVID-19 epidemic shows the need to construct models that reflect the dynamics of the studied ratios of infection rates, morbidity, recovery and mortality in the dynamics of the pandemic, taking into account the influence of external factors on this process. Most of the known mathematical models for predicting the spread and consequences of COVID-19 are compartmental models that implement sequential transitions between states with the allocation of groups of individuals with different affiliation to the progression/decline of the spread of infection. To compensate for the shortcomings of the compartmental models due to the assumption of population homogeneity and the lack of adequate approaches to the scalability of the simulation results, models based on the Monte Carlo method and the concept of multi- agent systems are used. The development of modelling methods is associated with the need to expand information support for healthcare professionals and health care organizers with the possibility of online configuration of parameters of mathematical models and the use of data from 3/4 cloud services with visualization of the results of modelling.

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新冠肺炎疫情传播的数学建模及预防措施保护老年人的生命和健康

基于数学建模的定量方法用于证明一系列措施的合理性，这些措施旨在证明在2019冠状病毒病大流行背景下保护老年人生命和健康的一系列预防措施的合理性。对2019冠状病毒病死率精算数学模型发展现状的分析表明，需要构建能够反映所研究的感染率、发病率、恢复率和死亡率在大流行动态中的动态模型，同时考虑外部因素对这一过程的影响。大多数已知的预测COVID-19传播和后果的数学模型都是隔室模型，通过分配与感染传播进展/下降有不同关系的个体群体，实现各州之间的顺序过渡。为了弥补分区模型由于假设人口同质性和缺乏足够的方法来模拟结果的可扩展性而造成的缺点，使用了基于蒙特卡罗方法和多智能体系统概念的模型。建模方法的发展与需要扩大对医疗保健专业人员和医疗保健组织者的信息支持有关，因为有可能在线配置数学模型的参数，并使用来自3/4云服务的数据，使建模结果可视化。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Bulletin of the South Ural State University Series-Mathematical Modelling Programming & Computer Software MATHEMATICS, APPLIED-

CiteScore

1.00

自引率

50.00%

发文量

期刊介绍： Series «Mathematical Modelling, Programming & Computer Software» of the South Ural State University Bulletin was created in 2008. Nowadays it is published four times a year. The basic goal of the editorial board as well as the editorial commission of series «Mathematical Modelling, Programming & Computer Software» is research promotion in the sphere of mathematical modelling in natural, engineering and economic science. Priority publication right is given to: -the results of high-quality research of mathematical models, revealing less obvious properties; -the results of computational research, containing designs of new computational algorithms relating to mathematical models; -program systems, designed for computational experiments.