Scholarlink

<p>The co-dynamics of COVID-19 and human Metapneumovirus (HMPV) pose a public health threat that can be caused by severe respiratory illness in vulnerable groups such as the elderly, children, and immune-weakened individuals. In this study, we present a mathematical model with the Caputo fractional derivative and use a semi-analytical Laplace-Adomian decomposition method (LADM) to obtain the approximate solutions and simulate the co-dynamics of two respiratory pathogens. The results are validated with real COVID-19 data for Bangladesh, revealing that the fractional-order model demonstrates optimal agreement at <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43994_2025_271_Article_IEq1.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="63" /> </InlineMediaObject> <EquationSource Format="TEX">\(\alpha =0.83\)</EquationSource> </InlineEquation>. The analysis highlights the impact of fractional-order dynamics on transmission rates, quarantine efficacy, and recovery trajectories. The study advances by integrating memory effects and providing a framework for evaluating intervention strategies. The results of this study suggest that the fractional-order model provides a more flexible framework with memory effects for multiple respiratory disease outbreaks.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A fractional-order model of COVID-19 and human Metapneumovirus co-dynamics: a Laplace-Adomian decomposition approach for epidemiological prediction and intervention analysis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年9月15日

查看全文
  • Sharmin Sultana Shanta,
  • M. Ali Akbar,
  • M. S. Osman

摘要

The co-dynamics of COVID-19 and human Metapneumovirus (HMPV) pose a public health threat that can be caused by severe respiratory illness in vulnerable groups such as the elderly, children, and immune-weakened individuals. In this study, we present a mathematical model with the Caputo fractional derivative and use a semi-analytical Laplace-Adomian decomposition method (LADM) to obtain the approximate solutions and simulate the co-dynamics of two respiratory pathogens. The results are validated with real COVID-19 data for Bangladesh, revealing that the fractional-order model demonstrates optimal agreement at \(\alpha =0.83\) . The analysis highlights the impact of fractional-order dynamics on transmission rates, quarantine efficacy, and recovery trajectories. The study advances by integrating memory effects and providing a framework for evaluating intervention strategies. The results of this study suggest that the fractional-order model provides a more flexible framework with memory effects for multiple respiratory disease outbreaks.