COVID-19大流行:基于饱和模型的不同大流行控制策略分析

S. Bracke, L. Grams
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引用次数: 0

摘要

2019年12月以来,全球面临2019冠状病毒病(COVID-19)疫情。2020年初,COVID-19疫情演变为大流行,并持续至今。在许多国家,为了控制大流行,制定了若干控制战略或这些战略的组合,如限制(如封锁行动)、医疗保健(如开发疫苗或药物)和医疗预防(如卫生概念)。根据选择的控制策略,COVID-19的传播行为在定义的时间范围内减慢或大致停止。这种现象被称为饱和效应,可以用饱和模型来描述:例如,一个基本的方法是Verhulst(1838)。模型参数允许以合理的方式解释扩散速度(增长)和饱和效应。本文展示了基于约翰霍普金斯大学数据库(2020年)对不同国家和不同时间阶段不同流行病控制策略下COVID-19传播行为和饱和效应的研究结果。该研究包括分析与短期有关的饱和效应,例如可能由封锁战略、地理影响和医疗预防活动引起的饱和效应。这项研究的重点是参考国家,如德国、日本、丹麦、冰岛、爱尔兰和以色列。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COVID-19 pandemic: Analyzing of different pandemic control strategies using saturation models
Since December 2019, the world is confronted with the outbreak of the respiratory disease COVID-19. At the beginning of 2020, the COVID-19 epidemic evolved into a pandemic, which continues to this day. Within many countries, several control strategies or combinations of them, like restrictions (e.g. lockdown actions), medical care (e.g. development of vaccine or medicaments) and medical prevention (e.g. hygiene concept), were established with the goal to control the pandemic. Depending on the chosen control strategy, the COVID-19 spreading behavior slowed down or approximately stopped for a defined time range. This phenomenon is called saturation effect and can be described by saturation models: E.g. a fundamental approach is Verhulst (1838). The model parameter allows the interpretation of the spreading speed (growth) and the saturation effect in a sound way. This paper shows results of a research study of the COVID-19 spreading behavior and saturation effects depending on different pandemic control strategies in different countries and time phases based on Johns Hopkins University data base (2020). The study contains the analyzing of saturation effects related to short time periods, e.g. possible caused by lockdown strategies, geographical influences and medical prevention activities. The research study is focusing on reference countries like Germany, Japan, Denmark, Iceland, Ireland and Israel.
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