Department of Mathematics, Faculty of Science, King Mongkut's University of Technology, Thonburi (KMUTT), 126 Pracha-Uthit Road, Bang Mod, Thrung Khru, Bangkok 10140, Thailand.
Department of Mathematics and Statistics, University of Swat, Khyber Pakhtunkhawa, Pakistan.
Math Biosci Eng. 2023 Apr 26;20(6):11281-11312. doi: 10.3934/mbe.2023500.
This study explores the use of numerical simulations to model the spread of the Omicron variant of the SARS-CoV-2 virus using fractional-order COVID-19 models and Haar wavelet collocation methods. The fractional order COVID-19 model considers various factors that affect the virus's transmission, and the Haar wavelet collocation method offers a precise and efficient solution to the fractional derivatives used in the model. The simulation results yield crucial insights into the Omicron variant's spread, providing valuable information to public health policies and strategies designed to mitigate its impact. This study marks a significant advancement in comprehending the COVID-19 pandemic's dynamics and the emergence of its variants. The COVID-19 epidemic model is reworked utilizing fractional derivatives in the Caputo sense, and the model's existence and uniqueness are established by considering fixed point theory results. Sensitivity analysis is conducted on the model to identify the parameter with the highest sensitivity. For numerical treatment and simulations, we apply the Haar wavelet collocation method. Parameter estimation for the recorded COVID-19 cases in India from 13 July 2021 to 25 August 2021 has been presented.
本研究使用分数阶 COVID-19 模型和 Haar 小波配置方法探索数值模拟在 Omicron 变异 SARS-CoV-2 病毒传播中的应用。分数阶 COVID-19 模型考虑了影响病毒传播的各种因素，而 Haar 小波配置方法为模型中使用的分数导数提供了精确高效的解决方案。模拟结果深入了解了 Omicron 变异的传播，为旨在减轻其影响的公共卫生政策和策略提供了有价值的信息。本研究标志着对 COVID-19 大流行动态和其变体出现的理解取得了重大进展。使用 Caputo 意义上的分数导数重新构建 COVID-19 流行模型，并通过考虑不动点理论结果来建立模型的存在性和唯一性。对模型进行了敏感性分析，以确定最敏感的参数。对于数值处理和模拟，我们应用 Haar 小波配置方法。给出了 2021 年 7 月 13 日至 2021 年 8 月 25 日印度记录的 COVID-19 病例的参数估计。
