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<p>Human behavior plays a pivotal role in shaping infectious disease outbreaks. Although vaccination is one of the most effective interventions, its success depends heavily on population compliance, which is strongly influenced by awareness and information dissemination. Existing vaccination–awareness models have considered media influence but have largely neglected the Peltzman effect—a behavioral phenomenon in which individuals, feeling protected, engage in riskier activities that offset the benefits of vaccination. To address this gap, we propose a novel SVEIR-A framework that explicitly incorporates both media-driven awareness and the Peltzman effect, offering a more realistic representation of behavioral dynamics in epidemic control. From a mathematical perspective, we derive the basic reproduction number, establish the stability conditions for both the disease-free and endemic equilibria, and determine an explicit expression for the herd immunity threshold. To calibrate the model, we conducted sensitivity analysis of 14 parameters, followed by subset selection and practical identifiability, which identified 10 estimable parameters. Using COVID-19 data from India across two epidemic phases (Phase 1: March 1–June 15, 2021, Phase 2: December 20, 2021–February 28, 2022), we estimated the sensitive parameters via constrained least-squares method in MATLAB using fmincon function. The fitting process achieved stable convergence, residual analysis confirmed good fitting, and estimated parameters were accompanied by 95% confidence intervals. Model performance metrics demonstrated strong fit quality and predictive accuracy across both phases, underscoring the robustness of the framework. Numerical simulations show that awareness-driven vaccination reduces disease prevalence, but its effectiveness is substantially undermined by the Peltzman effect, wherein individuals adopt riskier behavior post-vaccination. The influence of awareness and vaccination is phase-dependent—limited in early epidemic stages but highly significant in later waves. Importantly, the rapid deployment of high-efficacy vaccines during periods of high transmission yields the greatest reduction in cases.</p>

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Modeling vaccination behavior under media campaigns and the peltzman effect

  • 期刊论文

  • 发表日期：

    2026年1月9日

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  • Komal Tanwar,
  • Jai Prakash Tripathi

摘要

Human behavior plays a pivotal role in shaping infectious disease outbreaks. Although vaccination is one of the most effective interventions, its success depends heavily on population compliance, which is strongly influenced by awareness and information dissemination. Existing vaccination–awareness models have considered media influence but have largely neglected the Peltzman effect—a behavioral phenomenon in which individuals, feeling protected, engage in riskier activities that offset the benefits of vaccination. To address this gap, we propose a novel SVEIR-A framework that explicitly incorporates both media-driven awareness and the Peltzman effect, offering a more realistic representation of behavioral dynamics in epidemic control. From a mathematical perspective, we derive the basic reproduction number, establish the stability conditions for both the disease-free and endemic equilibria, and determine an explicit expression for the herd immunity threshold. To calibrate the model, we conducted sensitivity analysis of 14 parameters, followed by subset selection and practical identifiability, which identified 10 estimable parameters. Using COVID-19 data from India across two epidemic phases (Phase 1: March 1–June 15, 2021, Phase 2: December 20, 2021–February 28, 2022), we estimated the sensitive parameters via constrained least-squares method in MATLAB using fmincon function. The fitting process achieved stable convergence, residual analysis confirmed good fitting, and estimated parameters were accompanied by 95% confidence intervals. Model performance metrics demonstrated strong fit quality and predictive accuracy across both phases, underscoring the robustness of the framework. Numerical simulations show that awareness-driven vaccination reduces disease prevalence, but its effectiveness is substantially undermined by the Peltzman effect, wherein individuals adopt riskier behavior post-vaccination. The influence of awareness and vaccination is phase-dependent—limited in early epidemic stages but highly significant in later waves. Importantly, the rapid deployment of high-efficacy vaccines during periods of high transmission yields the greatest reduction in cases.