Epidemics modeling

P. Knopov, O. Bogdanov
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Abstract

Introduction. Due to the spread of COVID-19 in the world, mathematical modeling of epidemiological processes is an important and relevant scientific problem. There are many models describing the dynamics of pandemics, such as the standard SIR model, but most of them are deterministic, while in reality, the processes of infecting and recoveries are random in nature. Also, most of the models either do not include the existence of vaccines or medication or do not take into consideration the price of such medication. Sometimes, because of the high price, the widespread use of contemporary medication is impossible, especially in poor countries. In this case, there is a problem of finding a compromise between the purchase of a low amount of medication and a low amount of human deaths as a result of a pandemic. We propose a stochastic model, which describes this situation. The purpose of the paper is to develop a mathematical model corresponding to the minimization of losses from certain pandemics, as well as the analysis of such a model. Results. In this paper, we propose a stochastic model that describes the behavior of an epidemic with a certain amount of medication administered among the population. We present several estimates for the parameters of the epidemic, such as its duration and the total number of infected people at a certain time, given an initial number of infected people. The first two moments of the number of infected people at a given time were found. Furthermore, we found an estimate of the total losses as a result of the pandemic, which includes medication costs and losses from deaths. Several formulas are presented, which simplify the search for the minimal amount of medication needed to minimize the losses. Conclusions. The presented problem and its solution can be used for models of certain epidemics to minimize the medication costs and losses from deaths. Keywords: epidemic, epidemic modeling, loss minimization.
流行病建模
介绍由于新冠肺炎在世界范围内的传播,流行病学过程的数学建模是一个重要而相关的科学问题。有许多模型描述了流行病的动态,例如标准的SIR模型,但其中大多数是确定性的,而在现实中,感染和康复的过程本质上是随机的。此外,大多数模型要么不包括疫苗或药物的存在,要么不考虑此类药物的价格。有时,由于价格高昂,当代药物的广泛使用是不可能的,尤其是在贫穷国家。在这种情况下,存在着一个问题,即在购买少量药物和减少疫情造成的人类死亡之间找到折衷方案。我们提出了一个随机模型来描述这种情况。本文的目的是开发一个与某些流行病造成的损失最小化相对应的数学模型,以及对该模型的分析。后果在本文中,我们提出了一个随机模型,描述了在人群中服用一定药物的流行病的行为。在给定初始感染人数的情况下,我们对疫情的参数进行了几个估计,如持续时间和某个时间的感染总人数。发现了特定时间感染人数的前两个时刻。此外,我们发现了对疫情造成的总损失的估计,其中包括药物费用和死亡损失。提出了几个公式,简化了对所需最小药物量的搜索,以最大限度地减少损失。结论。所提出的问题及其解决方案可用于某些流行病的模型,以最大限度地减少药物成本和死亡损失。关键词:流行病,流行病建模,损失最小化。
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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20
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6 weeks
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