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使用带有疫苗接种的双毒株模型对新冠病毒动态进行建模。

Modeling COVID-19 dynamic using a two-strain model with vaccination.

作者信息

de León Ugo Avila-Ponce, Avila-Vales Eric, Huang Kuan-Lin

机构信息

Programa de Doctorado en Ciencias Biológicas, UNAM, Mexico City, Mexico.

Facultad de Matemáticas, Universidad Autónoma de Yucatán. Anillo Periférico Norte. Tablaje Catastral 13615, C.P. 97119. Mérida, Yucatán.

出版信息

Chaos Solitons Fractals. 2022 Apr;157:111927. doi: 10.1016/j.chaos.2022.111927. Epub 2022 Feb 16.

Abstract

Multiple strains of the SARS-CoV-2 have arisen and jointly influence the trajectory of the coronavirus disease (COVID-19) pandemic. However, current models rarely account for this multi-strain dynamics and their different transmission rate and response to vaccines. We propose a new mathematical model that accounts for two virus variants and the deployment of a vaccination program. To demonstrate utility, we applied the model to determine the control reproduction number and the per day infection, death and recovery rates of each strain in the US pandemic. The model dynamics predicted the rise of the alpha variant and shed light on potential impact of the delta variant in 2021. We obtained the minimum percentage of fully vaccinated individuals to reduce the spread of the variants in combination with other intervention strategies to deaccelerate the rise of a multi-strain pandemic.

摘要

严重急性呼吸综合征冠状病毒2(SARS-CoV-2)已出现多种毒株,并共同影响着冠状病毒病(COVID-19)大流行的发展轨迹。然而,当前模型很少考虑这种多毒株动态及其不同的传播率和对疫苗的反应。我们提出了一个新的数学模型,该模型考虑了两种病毒变体以及疫苗接种计划的实施情况。为了证明其效用,我们应用该模型来确定美国大流行中每种毒株的控制再生数以及每日感染、死亡和康复率。模型动态预测了阿尔法变体的出现,并揭示了2021年德尔塔变体的潜在影响。我们得出了完全接种疫苗个体的最低百分比,以结合其他干预策略减少变体的传播,从而减缓多毒株大流行的上升趋势。

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