创建COVID-19冠状病毒大流行预测模型的问题

E. Levkova, Е А Левкова, R. Sepiashvili, Р И Сепиашвили, S. Savin, С З Савин
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引用次数: 1

摘要

的相关性。本文致力于建立基于流行病学和免疫学数据的预后模型。目的:研究新型冠状病毒肺炎(COVID-19)患者的动态流行病学和免疫学特征。材料和方法。描述了采用多变量分析对COVID-19患者的流行病学和免疫学特征进行系统分析的方法学方法。所使用的计算机辅助分析系统技术、用于识别、测量和确定患者状况的算法以及统计数据处理方法,使得有可能创建一个通用信息预测模型,用于计算易于普遍化的传染病(大流行病)的动态,并了解这些新的传染病在哪些群体中最危险。结果和讨论。采用系统分析的方法,利用最客观的国际数据,对新型冠状病毒大流行预测模型的流行病学和免疫学方面进行评价,增加了分析的信息量。结论。为应对冠状病毒感染在俄罗斯传播所造成的医疗和社会后果,建立新冠肺炎大流行的预测流行病学和免疫学模型是一项紧迫而有希望的任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Problems of creating predictive models of the COVID19 coronavirus pandemic
Relevance. The article is devoted to creating prognostic models based on epidemiological and immunological data. Objective: to study the comparative dynamic epidemiological and immunological characteristics of patients with COVID-19. Materials and methods. Methodological approaches to the use of system analysis of epidemiological and immunological characteristics of patients with COVID-19 using multivariate analysis are described. The used technologies of computer-aided analysis systems, algorithms for recognizing, measuring and identifying the condition of patients, and methods of statistical data processing made it possible to create a universal information predictive model for calculating the dynamics of infectious diseases prone to generalization (pandemics), as well as to understand in which groups these new infectious diseases are most dangerous. Results and discussion. Using the methods of system analysis, the epidemiological and immunological aspects of predictive models of the coronavirus pandemic were evaluated using the most objective international data, which increased the information content of the analysis. Conclusions . Creating predictive epidemiological and immunological models of the pandemic is an urgent and promising task to combat the medical and social consequences of the spread of coronavirus infection in Russia.
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来源期刊
CiteScore
0.50
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0.00%
发文量
43
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8 weeks
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