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利用高斯脉冲对全球 COVID-19 疫情进行分析,建立时变传播率模型。

Modeling the time-dependent transmission rate using gaussian pulses for analyzing the COVID-19 outbreaks in the world.

机构信息

Department of Physics, FMIPA, Universitas Padjadjaran, Jalan Raya Bandung-Sumedang KM 21, Sumedang, 45363, Indonesia.

Department of Electrical Engineering, FMIPA, Universitas Padjadjaran, Jalan Raya Bandung-Sumedang KM 21, Sumedang, 45363, Indonesia.

出版信息

Sci Rep. 2023 Mar 18;13(1):4466. doi: 10.1038/s41598-023-31714-5.

Abstract

In this work, an SEIR epidemic model with time-dependent transmission rate parameters for the multiple waves of COVID-19 infection was investigated. It is assumed that the transmission rate is determined by the superposition of the Gaussian pulses. The interaction of these dynamics is represented by recursive equations. Analysis of the overall dynamics of disease spread is determined by the effective reproduction number R(t) produced throughout the infection period. The study managed to show the evolution of the epidemic over time and provided important information about the occurrence of multiple waves of COVID-19 infection in the world and Indonesia.

摘要

在这项工作中,研究了一个具有时变传播率参数的 SEIR 传染病模型,用于 COVID-19 感染的多波次。假设传播率由高斯脉冲的叠加决定。这些动力学的相互作用由递归方程表示。通过整个感染期产生的有效繁殖数 R(t)来确定疾病传播的整体动力学的分析。该研究成功地展示了随时间的流行演变,并提供了有关 COVID-19 在世界和印度尼西亚多次感染的发生的重要信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/baaa/10024739/f4f2f4e2f7a7/41598_2023_31714_Fig1_HTML.jpg

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