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Objectives <p>This study develops a fractional-order mathematical model using the Hilfer–Katugampola derivative to assess rotavirus transmission dynamics under booster vaccination strategies, addressing limitations of classical integer-order models in capturing memory effects and waning immunity.</p> Methodology <p>We formulated a compartmental model with five states (Susceptible, Vaccinated, Boosted, Infected, Recovered) using Hilfer–Katugampola fractional derivatives. The basic reproduction number <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\({R}_{0}\)</EquationSource> </InlineEquation> was derived analytically, and stability conditions were established. Numerical simulations employed predictor–corrector methods with parameters estimated from epidemiological data.</p> Results <p>The fractional-order model demonstrated superior flexibility in capturing real-world transmission patterns, with memory effects reducing peak infections by 15–25% compared to integer-order models (based on baseline parameter set with <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\alpha =0.85\)</EquationSource> </InlineEquation>). Optimal booster administration at 3 months post-primary vaccination reduced disease prevalence by 42.3% compared to no booster strategy. Sensitivity analysis identified fractional order <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\alpha \)</EquationSource> </InlineEquation> and booster timing <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\psi \)</EquationSource> </InlineEquation> as critical parameters influencing <InlineEquation ID="IEq5"> <EquationSource Format="TEX">\({R}_{0}\)</EquationSource> </InlineEquation>.</p> Conclusions <p>Hilfer–Katugampola fractional modeling provides a flexible framework for rotavirus dynamics prediction. Optimized booster strategies informed by fractional calculus can reduce disease burden by approximately 40% (under baseline scenarios), offering valuable insights for public health planning in high-burden regions.</p>

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Modeling rotavirus transmission with booster vaccination using Hilfer–Katugampola fractional derivatives: a public health perspective

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月8日

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  • Samaira Naz,
  • Aamir Nadim

摘要

Objectives

This study develops a fractional-order mathematical model using the Hilfer–Katugampola derivative to assess rotavirus transmission dynamics under booster vaccination strategies, addressing limitations of classical integer-order models in capturing memory effects and waning immunity.

Methodology

We formulated a compartmental model with five states (Susceptible, Vaccinated, Boosted, Infected, Recovered) using Hilfer–Katugampola fractional derivatives. The basic reproduction number \({R}_{0}\) was derived analytically, and stability conditions were established. Numerical simulations employed predictor–corrector methods with parameters estimated from epidemiological data.

Results

The fractional-order model demonstrated superior flexibility in capturing real-world transmission patterns, with memory effects reducing peak infections by 15–25% compared to integer-order models (based on baseline parameter set with \(\alpha =0.85\) ). Optimal booster administration at 3 months post-primary vaccination reduced disease prevalence by 42.3% compared to no booster strategy. Sensitivity analysis identified fractional order \(\alpha \) and booster timing \(\psi \) as critical parameters influencing \({R}_{0}\) .

Conclusions

Hilfer–Katugampola fractional modeling provides a flexible framework for rotavirus dynamics prediction. Optimized booster strategies informed by fractional calculus can reduce disease burden by approximately 40% (under baseline scenarios), offering valuable insights for public health planning in high-burden regions.