Biala T A, Khaliq A Q M
Center for Computational Science and Department of Mathematical Sciences, Middle Tennessee State University, Murfreesboro, TN 37132-0001, USA.
Commun Nonlinear Sci Numer Simul. 2021 Jul;98:105764. doi: 10.1016/j.cnsns.2021.105764. Epub 2021 Feb 19.
We propose a time-fractional compartmental model (SEI I HRD) comprising of the susceptible, exposed, infected (asymptomatic and symptomatic), hospitalized, recovered and dead population for the COVID-19 pandemic. We study the properties and dynamics of the proposed model. The conditions under which the disease-free and endemic equilibrium points are asymptotically stable are discussed. Furthermore, we study the sensitivity of the parameters and use the data from Tennessee state (as a case study) to discuss identifiability of the parameters of the model. The non-negative parameters in the model are obtained by solving inverse problems with empirical data from California, Florida, Georgia, Maryland, Tennessee, Texas, Washington and Wisconsin. The basic reproduction number is seen to be slightly above the critical value of one suggesting that stricter measures such as the use of face-masks, social distancing, contact tracing, and even longer stay-at-home orders need to be enforced in order to mitigate the spread of the virus. As stay-at-home orders are rescinded in some of these states, we see that the number of cases began to increase almost immediately and may continue to rise until the end of the year 2020 unless stricter measures are taken.
我们提出了一个时间分数阶 compartmental 模型(SEI I HRD),该模型包含了 COVID-19 大流行中的易感人群、暴露人群、感染人群(无症状和有症状)、住院人群、康复人群和死亡人群。我们研究了所提出模型的性质和动态。讨论了无病平衡点和地方病平衡点渐近稳定的条件。此外,我们研究了参数的敏感性,并使用田纳西州的数据(作为案例研究)来讨论模型参数的可识别性。通过使用来自加利福尼亚州、佛罗里达州、佐治亚州、马里兰州、田纳西州、得克萨斯州、华盛顿州和威斯康星州的经验数据求解反问题,得到了模型中的非负参数。基本再生数略高于临界值 1,这表明需要实施更严格的措施,如佩戴口罩、保持社交距离、接触者追踪,甚至更长时间的居家令,以减轻病毒的传播。随着其中一些州取消居家令,我们看到病例数几乎立即开始增加,并且可能会继续上升,直到 2020 年底,除非采取更严格的措施。