一类具有无症状感染和隔离的 SIAQR 传播模型动力学分析和最优控制

Abstract

Abstract:

This paper presents an epidemic model with asymptomatic infection and isolation in the context of population transmission of a Corona Virus Disease 2019 (COVID-19), we analyze the basic reproduction number of the model, the final epidemic size, the existence and uniqueness and solvability of the solution for the implicit final size equation. On this basis, we consider two possible control strategies and analyze the existence of optimal control by using the Filippov-Cesari existence theorem and Pontryagin extreme principle. Base on the historical data of COVID-19 infection in Zhejiang Province, the model parameters are estimated using the Markov Chain Monte Carlo method. The numerical simulation results show that the control strategy can reduce the peak isolation rate by 33.92% and final epidemic size by 76.54%. This suggests that reducing transmission rates and vaccinating susceptible individuals are still effective means of controlling the development of COVID-19 outbreaks, and provides recommendations for controlling COVID-19 outbreaks and responding to emerging infectious diseases.

Key words: Asymptomatic infection, Isolation, Basic reproduction number, Final size equation, Optimal control

CLC Number:

O175

Zhong Yi, Wang Yi, Jiang Tianhe. Dynamic Analysis and Optimal Control of an SIAQR Transmission Model with Asymptomatic Infection and Isolation[J].Acta mathematica scientia,Series A, 2023, 43(6): 1914-1928.

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Dynamic Analysis and Optimal Control of an SIAQR Transmission Model with Asymptomatic Infection and Isolation

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