Targeted COVID-19 Vaccination (TAV-COVID) Considering Limited Vaccination Capacities-An Agent-Based Modeling...

Area of Science:

• Epidemiology and Public Health
• Mathematical Modeling
• Vaccinology

Background:

• Limited COVID-19 vaccine availability in Austria necessitates strategic allocation.
• The study addresses the need for evidence-based guidance to reduce COVID-19 morbidity and mortality.

Purpose of the Study:

• To compare various COVID-19 vaccination strategies.
• To identify an optimal vaccination prioritization sequence to minimize hospitalizations and deaths in Austria.
• To guide public health authorities in vaccine deployment.

Main Methods:

• A dynamic agent-based population model was employed to simulate different vaccination strategies.
• Vaccination was targeted to specific age groups (elderly, middle-aged, younger), vulnerable individuals, and healthcare workers (HCW).
• Optimization was performed for initial vaccine batches and larger-scale deployment (2.45 million individuals), considering vaccine effectiveness and immunity types.

Main Results:

• Maximum reduction in COVID-19 hospitalizations and deaths was achieved by prioritizing the elderly and vulnerable, followed by middle-aged individuals, HCW, and younger groups.
• This prioritization sequence, applied to 2.45 million individuals, was projected to avoid approximately one-third of total deaths and hospitalizations.
• Prioritizing HCW first offered greater occupational safety but resulted in slightly lower overall reductions in mortality and hospitalizations.

Conclusions:

• Elderly and vulnerable populations should be prioritized for COVID-19 vaccination to maximize the reduction of hospitalizations and deaths.
• The findings provide a clear prioritization strategy for vaccine rollout, especially when supplies are constrained.
• The study underscores the importance of targeted vaccination strategies in pandemic response.