Saha Pritam, Biswas Sudhanshu Kumar, Biswas Md Haider Ali, Ghosh Uttam
Department of Applied Mathematics, University of Calcutta, Kolkata, 700009 India.
Department of Mathematics, Sripat Singh College, Murshidabad, India.
Nonlinear Dyn. 2023;111(7):6873-6893. doi: 10.1007/s11071-022-08181-0. Epub 2023 Jan 7.
During the COVID-19 pandemic, one of the major concerns was a medical emergency in human society. Therefore it was necessary to control or restrict the disease spreading among populations in any fruitful way at that time. To frame out a proper policy for controlling COVID-19 spreading with limited medical facilities, here we propose an model having saturated treatment. We check biological feasibility of model solutions and compute the basic reproduction number ( ). Moreover, the model exhibits transcritical, backward bifurcation and forward bifurcation with hysteresis with respect to different parameters under some restrictions. Further to validate the model, we fit it with real COVID-19 infected data of Hong Kong from 19th December, 2021 to 3rd April, 2022 and estimate model parameters. Applying sensitivity analysis, we find out the most sensitive parameters that have an effect on . We estimate using actual initial growth data of COVID-19 and calculate effective reproduction number for same period. Finally, an optimal control problem has been proposed considering effective vaccination and saturated treatment for hospitalized class to decrease density of the infected class and to minimize implemented cost.
在新冠疫情期间,人类社会面临的一个主要担忧是医疗紧急情况。因此,当时有必要以任何有效的方式控制或限制疾病在人群中的传播。为了在医疗设施有限的情况下制定出控制新冠病毒传播的适当政策,我们在此提出一个具有饱和治疗的模型。我们检验模型解的生物学可行性并计算基本再生数( )。此外,在某些限制条件下,该模型针对不同参数呈现出跨临界、反向分岔和带有滞后现象的正向分岔。为了进一步验证该模型,我们将其与香港2021年12月19日至2022年4月3日的实际新冠病毒感染数据进行拟合,并估计模型参数。通过应用敏感性分析,我们找出了对 有影响的最敏感参数。我们利用新冠病毒的实际初始增长数据估计 ,并计算同一时期的有效再生数。最后,提出了一个最优控制问题,考虑对住院患者进行有效疫苗接种和饱和治疗,以降低感染人群的密度并使实施成本最小化。