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

利用高斯脉冲对随时间变化的传播率进行建模,以分析全球新冠肺炎疫情爆发情况

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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(e)(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.

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