Constrained optimal control applied to vaccination for influenza

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Influenza pandemics pose significant public health challenges.
• Efficient vaccine distribution and administration are critical for pandemic mitigation.
• Real-world constraints like limited coverage and daily capacity affect vaccination strategies.

Purpose of the Study:

• To develop an optimal control strategy for influenza vaccination under realistic constraints.
• To minimize the number of infected individuals while accounting for intervention costs.
• To analyze time-dependent vaccination policies considering population heterogeneity.

Main Methods:

• Formulation of an optimal control problem with mixed state and control variable constraints.
• Incorporation of population heterogeneity into the influenza model.
• Computation and analysis of time-dependent vaccination schedules.

Main Results:

• The study provides a framework for optimizing vaccine deployment under practical limitations.
• Identified optimal vaccination strategies that balance infection reduction and cost.
• Demonstrated the impact of transmissibility, coverage, and time delays on vaccination effectiveness.

Conclusions:

• Optimal control models can effectively guide influenza vaccine prioritization and scheduling.
• Realistic constraints are essential for practical and impactful public health interventions.
• Heterogeneity in population structure influences the optimal vaccination strategy.