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印度 COVID-19 变种的双重菌株动态:建模、分析及对大流行控制的影响。

Dual-strain dynamics of COVID-19 variants in India: Modeling, analysis, and implications for pandemic control.

机构信息

Department of Mathematics, National Institute of Technology, Uttarakhand, Srinagar (Garhwal), Uttarakhand 246174, India.

Department of Mathematics and Science Education, Harran University, 63190 Sanliurfa, Turkey.

出版信息

Gene. 2024 Oct 30;926:148586. doi: 10.1016/j.gene.2024.148586. Epub 2024 May 22.

Abstract

This study introduces a detailed compartmental model developed to understand the complex dynamics of COVID-19 transmission, focusing on the Delta and Omicron variants in India. The model tracks disease progression through different population compartments, considering factors like vaccination, time-dependent transmission, economic burden and COVID-19 death rates, loss of vaccine-induced immunity, and the transition of asymptomatic cases to recovery. The model is validated against established epidemiological knowledge and real-world data, emphasizing dynamic parameterization and accurate representation of immunity dynamics. The basic reproduction number for both variants is calculated, and sensitivity analysis for various parameters is conducted. Time-dependent parameters are estimated using the discrete inverse method. The study also explores the economic burden, impact of different types of masks, vaccine efficacy, and vaccine-induced immunity through numerical analysis.

摘要

本研究介绍了一个详细的房室模型,旨在理解 COVID-19 传播的复杂动态,重点关注印度的 Delta 和 Omicron 变体。该模型通过不同的人群隔室跟踪疾病进展,考虑了疫苗接种、时变传播、经济负担和 COVID-19 死亡率、疫苗诱导免疫丧失以及无症状病例向康复的转变等因素。该模型经过了既定的流行病学知识和现实世界数据的验证,强调了动态参数化和对免疫动力学的准确表示。计算了两种变体的基本繁殖数,并对各种参数进行了敏感性分析。使用离散逆方法估计时变参数。该研究还通过数值分析探讨了经济负担、不同类型口罩的影响、疫苗效力和疫苗诱导免疫。

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