Multi-strain Epidemic Model with Immune Escape and Booster Optimization

Abstract

The emergence of multiple pathogen strains with varying transmissibility and immune escape capabilities presents significant challenges for epidemic control. This study proposes a multi-strain epidemic modeling framework that explicitly incorporates immune escape dynamics and booster vaccination strategies to evaluate optimal intervention policies. The model extends classical compartmental structures by allowing strain-specific transmission, partial cross-immunity, and waning immune protection following infection or vaccination. Immune escape is represented through reduced susceptibility parameters that vary across strains and immunity states, enabling the assessment of reinfection risk and breakthrough infections. Booster vaccination is incorporated as a time-dependent intervention that restores or enhances immune protection, with optimization scenarios exploring the timing, coverage, and target populations for booster deployment. Model parameters are informed by epidemiological data and existing immunological evidence. Simulation results indicate that strains with higher immune escape potential can substantially alter epidemic trajectories, leading to recurrent waves even in highly immunized populations. Strategically timed booster campaigns significantly mitigate these effects, reducing peak incidence and cumulative infections, particularly when prioritized for high-risk or high-contact groups. The findings highlight the importance of adaptive vaccination strategies in the presence of evolving pathogens. This modeling framework provides a quantitative tool for evaluating booster optimization and strain-specific control measures, offering actionable insights for public health planning in the context of emerging and immune-evasive infectious diseases.