Olayiwola Morufu Oyedunsi, Alaje Adedapo Ismaila, Olarewaju Akeem Yunus, Adedokun Kamilu Adewale
Department of Mathematical Sciences, Osun State University, Osogbo, Nigeria.
Healthc Anal (N Y). 2023 Nov;3:100179. doi: 10.1016/j.health.2023.100179. Epub 2023 Apr 20.
The recent global Coronavirus disease (COVID-19) threat to the human race requires research on preventing its reemergence without affecting socio-economic factors. This study proposes a fractional-order mathematical model to analyze the impact of high-risk quarantine and vaccination on COVID-19 transmission. The proposed model is used to analyze real-life COVID-19 data to develop and analyze the solutions and their feasibilities. Numerical simulations study the high-risk quarantine and vaccination strategies and show that both strategies effectively reduce the virus prevalence, but their combined application is more effective. We also demonstrate that their effectiveness varies with the volatile rate of change in the system's distribution. The results are analyzed using Caputo fractional order and presented graphically and extensively analyzed to highlight potent ways of curbing the virus.
近期全球冠状病毒病(COVID-19)对人类的威胁要求开展相关研究,即在不影响社会经济因素的情况下预防其再次出现。本研究提出了一个分数阶数学模型,以分析高风险隔离和疫苗接种对COVID-19传播的影响。所提出的模型用于分析实际的COVID-19数据,以开发和分析解决方案及其可行性。数值模拟研究了高风险隔离和疫苗接种策略,结果表明这两种策略均能有效降低病毒流行率,但联合应用更为有效。我们还证明,它们的有效性会随系统分布变化的波动率而变化。使用卡普托分数阶对结果进行分析,并以图形方式呈现且进行了广泛分析,以突出遏制该病毒的有效方法。