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<p>This study develops an age–stratified SEIR framework with dose–dependent recovery to explore how therapeutic allocation across age groups can mitigate epidemic spread. The susceptible and exposed classes are modeled as a single homogeneous pool, while infectious and recovered individuals are partitioned into four age groups (infants, children, adolescents, adults) with distinct recovery rates. Recovery in each age class is governed by a sigmoid dose–response relationship, representing age–specific pharmacodynamic efficacy as a function of administered dose. We derive an explicit expression for the basic reproduction number <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\mathcal{R}_0\)</EquationSource> </InlineEquation>, identify the corresponding transmission threshold <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\beta_c\)</EquationSource> </InlineEquation>, and characterize the forward threshold at <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\mathcal{R}_0=1\)</EquationSource> </InlineEquation> separating disease-free extinction from transient epidemic waves with age-stratified quasi-steady plateaus. Numerical simulations, including time series and low–dimensional phase portraits, illustrate how improving recovery in high–contribution age groups (particularly infants and children) can reduce <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\mathcal{R}_0\)</EquationSource> </InlineEquation> and suppress epidemic peaks under a range of initial conditions. The results provide a conceptual quantitative framework for assessing age–specific dosing strategies and highlight the need for disease – and setting–specific calibration before drawing operational policy conclusions.</p>

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Targeted epidemic mitigation through age-specific dose-response recovery modeling

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月13日

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  • Kalpana Umapathy,
  • Prabu Selvam,
  • Akiladevi Natarajan,
  • Prasantha Bharathi Dhandapani,
  • Rebecca Muhumuza Nalule

摘要

This study develops an age–stratified SEIR framework with dose–dependent recovery to explore how therapeutic allocation across age groups can mitigate epidemic spread. The susceptible and exposed classes are modeled as a single homogeneous pool, while infectious and recovered individuals are partitioned into four age groups (infants, children, adolescents, adults) with distinct recovery rates. Recovery in each age class is governed by a sigmoid dose–response relationship, representing age–specific pharmacodynamic efficacy as a function of administered dose. We derive an explicit expression for the basic reproduction number \(\mathcal{R}_0\) , identify the corresponding transmission threshold \(\beta_c\) , and characterize the forward threshold at \(\mathcal{R}_0=1\) separating disease-free extinction from transient epidemic waves with age-stratified quasi-steady plateaus. Numerical simulations, including time series and low–dimensional phase portraits, illustrate how improving recovery in high–contribution age groups (particularly infants and children) can reduce \(\mathcal{R}_0\) and suppress epidemic peaks under a range of initial conditions. The results provide a conceptual quantitative framework for assessing age–specific dosing strategies and highlight the need for disease – and setting–specific calibration before drawing operational policy conclusions.