Parameter identifiability of a within-host SARS-CoV-2 epidemic model

作     者：Junyuan Yang Sijin Wu Xuezhi Li Xiaoyan Wang Xue-Song Zhang Lu Hou 

作者机构：Complex Systems Research CenterShanxi UniversityTaiyuan030006China Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and PreventionShanxi UniversityTaiyuan030006China School of Mathematics and ScienceHenan Normal UniversityXinxiang453000China School of InformationShanxi University of Finance and EconomicsTaiyuan030006China Agriculture and Animal Husbandry Technology Promotion Center of Xingan LeagueXingan League137400China 

出 版 物：《Infectious Disease Modelling》 (传染病建模（英文）)

年 卷 期：2024年第9卷第3期

页      面：975-994页

核心收录：

学科分类：1007[医学-药学(可授医学、理学学位)] 100705[医学-微生物与生化药学] 1001[医学-基础医学(可授医学、理学学位)] 100103[医学-病原生物学] 10[医学] 

基　　金：This work is partially supported by Humanities and Social Foundation of Ministry of Education of China(22YJAZH129) the National Natural Science Foundation of China(No.12271143,No.61573016) the Shanxi Province Science Foundation(No.20210302123454) Shanxi Scholarship Council of China(2023–024) 

主　　题：Structural identifiability Practical identifiability Sensitivity analysis The basic reproduction number 

摘      要：Parameter identification involves the estimation of undisclosed parameters within a system based on observed data and mathematical *** this investigation,we employ DAISY to meticulously examine the structural identifiability of parameters of a within-host SARS-CoV-2 epidemic model,taking into account an array of observable ***,Monte Carlo simulations are performed to offer a comprehensive practical analysis of model ***,sensitivity analysis is employed to ascertain that decreasing the replication rate of the SARS-CoV-2 virus and curbing the infectious period are the most efficacious measures in alleviating the dissemination of COVID-19 amongst hosts.