Song Haitao, Wang Ruifeng, Liu Shengqiang, Jin Zhen, He Daihai
Complex Systems Research Center, Shanxi University, Taiyuan 030006, China.
Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on disease Control and Prevention, Shanxi University, Taiyuan 030006, China.
Results Phys. 2022 Nov;42:106011. doi: 10.1016/j.rinp.2022.106011. Epub 2022 Sep 24.
COVID-19 pandemic remains serious around the world and causes huge deaths and economic losses. To investigate the effect of vaccination and isolation delays on the transmission of COVID-19, we propose a mathematical model of COVID-19 transmission with vaccination and isolation delays. The basic reproduction number is computed, and the global dynamics of the model are proved. When , the disease-free equilibrium is globally asymptotically stable. The unique endemic equilibrium is globally asymptotically stable if . Based on the public information, parameter values are estimated, and sensitivity analysis is carried out by the partial rank correlation coefficients (PRCCs) and the extended version of the Fourier amplitude sensitivity test (eFAST). Our results suggest that the isolation rates of asymptomatic and symptomatic infectious individuals have a significant impact on the transmission of COVID-19. When the COVID-19 is epidemic, the optimal control strategies of our model with vaccination and isolation delays are analyzed. Under the limited resource with constant and time-varying isolation rates, we find that the optimal isolation rates may minimize the cumulative number of infected individuals and the cost of disease control, and effectively contain the transmission of COVID-19. Our study may help public health to prevent and control the COVID-19 spread.
新冠疫情在全球范围内仍然严峻,造成了巨大的死亡人数和经济损失。为了研究疫苗接种和隔离延迟对新冠病毒传播的影响,我们提出了一个包含疫苗接种和隔离延迟的新冠病毒传播数学模型。计算了基本再生数,并证明了该模型的全局动态性。当 时,无病平衡点是全局渐近稳定的。如果 ,唯一的地方病平衡点是全局渐近稳定的。基于公开信息,估计了参数值,并通过偏秩相关系数(PRCCs)和傅里叶振幅敏感性测试扩展版(eFAST)进行了敏感性分析。我们的结果表明,无症状和有症状感染个体的隔离率对新冠病毒的传播有显著影响。当新冠疫情流行时,分析了我们这个包含疫苗接种和隔离延迟模型的最优控制策略。在隔离率恒定和时变的资源有限情况下,我们发现最优隔离率可能会使感染个体累计数和疾病控制成本最小化,并有效遏制新冠病毒的传播。我们的研究可能有助于公共卫生部门预防和控制新冠疫情的蔓延。