Indirect Effects in Health Economic Models of Vaccines: Should We Include Them, and How Do We Model Them?

Area of Science:

• Epidemiology
• Health Economics
• Mathematical Modeling

Background:

• Indirect effects of vaccination (herd protection, serotype replacement, age shifts) significantly influence real-world program effectiveness.
• Economic evaluations often exclude indirect effects due to complexity, data limitations, and confounding factors.
• Accurate assessment of vaccination program impact requires accounting for these population-level dynamics.

Purpose of the Study:

• To compare static and dynamic transmission models (DTMs) for incorporating indirect vaccination effects in economic evaluations.
• To illustrate the influence of modeling choices on epidemiological and economic outcomes.
• To advocate for improved data and methodological guidelines for modeling indirect effects.

Main Methods:

• Review and comparison of static and dynamic transmission models (DTMs).
• Case studies illustrating model applications, strengths, and limitations.
• Analysis of how model structure, data, and parameters affect outcome projections.

Main Results:

• Static models are simpler but may miss crucial temporal and population dynamics.
• DTMs capture complex factors like population mixing and serotype competition but require more data and complexity.
• Modeling choices significantly impact projected epidemiological and economic outcomes, potentially leading to divergent conclusions.

Conclusions:

• There is a recognized need for including indirect effects in economic evaluations of vaccination programs.
• Limited methodological guidance from advisory and assessment bodies hinders consistent implementation.
• Collaborative efforts are needed to generate high-quality data and establish guidelines for modeling indirect effects to improve evidence-based decision-making.