利用TVBG-SEIR样条模型分析COVID-19传播情景

Q2 Agricultural and Biological Sciences
O. Kounchev, G. Simeonov, Z. Kuncheva
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引用次数: 7

摘要

我们建立了一种新的TVBG-SEIR样条模型,用于分析冠状病毒感染(COVID-19)。它旨在分析通过当局采取封锁/开放措施“控制”的流行病的长期全球演变。结合不同时间的不同“封锁情景”,不仅可以分析主要的流行病波,还可以分析正在出现的第二波和任何进一步的波。该模型由基于网络的COVID-19情景构建工具(简称sbt - COVID-19)提供,可作为(卫生)政策制定者探索各种情景的决策支持软件。这可以通过控制/改变遏制措施(家庭和社会隔离/检疫、旅行限制等)的规模和评估其有效性来实现。特别是,sbt - covid - 19工具允许评估封锁措施应维持多长时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scenarios for the spread of COVID-19 analyzed by the TVBG-SEIR spline model
We develop a novel TVBG-SEIR spline model for analysis of the coronavirus infection (COVID-19). It aims to analyze the long-term global evolution of the epidemics "controlled" by the introduction of lockdown/open up measures by the authorities. The incorporation of different "lockdown scenarios" varying in time permits to analyze not only the primary epidemic wave but also the arising secondary wave and any further waves.The model is supplied by a web-based Scenario Building Tool for COVID-19 (called shortly SBT-COVID19) which may be used as a decision support software by (health) policy makers to explore various scenarios. This can be achieved by controlling/changing the scale of the containment measures (home and social isolation/quarantine, travel restrictions and other) and to assess their effectiveness. In particular, the SBT-COVID19 Tool permits to assess how long the lockdown measures should be maintained.
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来源期刊
Biomath
Biomath Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)
CiteScore
2.20
自引率
0.00%
发文量
6
审稿时长
20 weeks
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