基于免疫流行病学模型的COVID-19疫情预测

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Samiran Ghosh, M. Banerjee, V. Volpert
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引用次数: 9

摘要

我们开发了一个新的数据驱动的免疫流行病学模型,该模型具有由流行病学,临床和实验数据确定的分布式传染性,恢复率和死亡率。人口中的免疫力通过接种不同剂量疫苗的人数随时间的变化以及通过康复个体的获得性免疫力来考虑。利用现有数据对模型进行了验证。我们表明,自COVID-19大流行开始以来,一些国家首次实现了集体免疫。然而,由于新变体BA.2的出现,与先前的BA.1变体相比,其免疫逃逸率或疾病传播率更高,疫情仍在继续。由于免疫力下降,预计几个月后会爆发大规模流行病。这些暴发可通过加强疫苗接种加以控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Immuno-epidemiological model-based prediction of further COVID-19 epidemic outbreaks due to immunity waning
We develop a new data-driven immuno-epidemiological model with distributed infectivity, recovery and death rates determined from the epidemiological, clinical and experimental data. Immunity in the population is taken into account through the time-dependent number of vaccinated people with different numbers of doses and through the acquired immunity for recovered individuals. The model is validated with the available data. We show that for the first time from the beginning of pandemic COVID-19 some countries reached collective immunity. However, the epidemic continues because of the emergence of new variant BA.2 with a larger immunity escape or disease transmission rate than the previous BA.1 variant. Large epidemic outbreaks can be expected several months later due to immunity waning. These outbreaks can be restrained by an intensive booster vaccination.
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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