预测消除不断进化的病毒变体。

IF 0.8 4区 数学 Q4 BIOLOGY
Elliott Hughes, Rachelle Binny, Shaun Hendy, Alex James
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引用次数: 0

摘要

随着SARS-CoV-2病毒在世界各地的传播,新的变种经常出现。虽然一些国家已经非常迅速和成功地开展了疫苗接种运动,但在全球范围内,绝大多数人口未接种疫苗,而且新的变种对现有的疫苗具有更强的抵抗力。我们提出了一个简单的疾病传播模型,其中包括一种新病毒的新变种的进化和对这些新毒株的不同疫苗有效性。我们表明,针对新菌株的快速疫苗更新比缓慢更新更有效,并且在提供这些疫苗时,通过非药物干预措施遏制传播至关重要。最后,当难以测量关键模型输入时,例如新突变和引起关注的变体出现的速度时,我们展示了可观察到的模型输出,即已观察到的新变体的数量,如何与病毒被消除的可能性密切相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting elimination of evolving virus variants.

As the SARS-CoV-2 virus spreads around the world new variants are appearing regularly. Although some countries have achieved very swift and successful vaccination campaigns, on a global scale the vast majority of the population is unvaccinated and new variants are proving more resistant to the current set of vaccines. We present a simple model of disease spread, which includes the evolution of new variants of a novel virus and varying vaccine effectiveness to these new strains. We show that rapid vaccine updates to target new strains are more effective than slow updates and containing spread through non-pharmaceutical interventions is vital while these vaccines are delivered. Finally, when measuring the key model inputs, e.g. the rate at which new mutations and variants of concern emerge, is difficult we show how an observable model output, the number of new variants that have been seen, is strongly correlated with the probability the virus is eliminated.

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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
15
审稿时长
>12 weeks
期刊介绍: Formerly the IMA Journal of Mathematics Applied in Medicine and Biology. Mathematical Medicine and Biology publishes original articles with a significant mathematical content addressing topics in medicine and biology. Papers exploiting modern developments in applied mathematics are particularly welcome. The biomedical relevance of mathematical models should be demonstrated clearly and validation by comparison against experiment is strongly encouraged. The journal welcomes contributions relevant to any area of the life sciences including: -biomechanics- biophysics- cell biology- developmental biology- ecology and the environment- epidemiology- immunology- infectious diseases- neuroscience- pharmacology- physiology- population biology
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