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研究广义年龄组传播模型中变异进化的影响。

Studying the impacts of variant evolution for a generalized age-group transmission model.

机构信息

School of Mathematics and Statistics, Fuzhou University, Fuzhou, Fujian, China.

Center for Applied Mathematics of Fujian Province, Fuzhou University, Fuzhou, Fujian, China.

出版信息

PLoS One. 2024 Jul 5;19(7):e0306554. doi: 10.1371/journal.pone.0306554. eCollection 2024.

Abstract

The differences of SARS-CoV-2 variants brought the changes of transmission characteristics and clinical manifestations during the prevalence of COVID-19. In order to explore the evolution mechanisms of SARS-CoV-2 variants and the impacts of variant evolution, the classic SIR (Susceptible-Infected-Recovered) compartment model was modified to a generalized SVEIR (Susceptible-Vaccinated-Exposed-Infected-Recovered) compartment model with age-group and varying variants in this study. By using of the SVEIR model and least squares method, the optimal fittings against the surveillance data from Fujian Provincial Center for Disease Control and Prevention were performed for the five epidemics of Fujian Province. The main epidemiological characteristics such as basic reproduction number, effective reproduction number, sensitivity analysis, and cross-variant scenario investigations were extensively investigated during dynamic zero-COVID policy. The study results showed that the infectivities of the variants became fast from wild strain to the Delta variant, further to the Omicron variant. Meanwhile, the cross-variant investigations showed that the average incubation periods were shortened, and that the infection scales quickly enhanced. Further, the risk estimations with the new variants were performed without implements of the non-pharmaceutical interventions, based on the dominant variants XBB.1.9.1 and EG.5. The results of the risk estimations suggested that non-pharmaceutical interventions were necessary on the Chinese mainland for controlling severe infections and deaths, and also that the regular variant monitors were still workable against the aggressive variant evolution and the emergency of new transmission risks in the future.

摘要

SARS-CoV-2 变异株的差异导致 COVID-19 流行期间传播特征和临床表现发生变化。为了探索 SARS-CoV-2 变异株的进化机制及其对变异进化的影响,本研究将经典 SIR(易感-感染-恢复) compartment 模型修改为具有年龄组和不同变异株的广义 SVEIR(易感-接种-暴露-感染-恢复) compartment 模型。通过使用 SVEIR 模型和最小二乘法,对福建省疾病预防控制中心的监测数据进行了最佳拟合,以拟合福建省的五次疫情。在动态零 COVID 政策下,广泛研究了基本繁殖数、有效繁殖数、敏感性分析和跨变异情景调查等主要流行病学特征。研究结果表明,变异株的传染性从野生株到 Delta 变异株再到奥密克戎变异株变得越来越快。同时,跨变异株调查显示,潜伏期平均缩短,感染规模迅速增强。此外,在不实施非药物干预措施的情况下,基于主要变异株 XBB.1.9.1 和 EG.5,对新变异株进行了风险估计。风险估计结果表明,非药物干预措施对于控制中国大陆的严重感染和死亡是必要的,而且针对未来具有攻击性的变异进化和新传播风险的紧急情况,定期的变异监测仍然是可行的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/09a3/11226140/e79e2ccbbccb/pone.0306554.g001.jpg

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