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Conference Paper

Model-Driven Approach to COVID-19 Vaccination Planning Leveraging Multi-Objective Optimization and Deep Learning

Feb 28, 2022

DOI:

Published in: Small Systems Simulation Symposium (SSSS)

Nenad Petrovic / Issam Al-Azzoni

Vaccination is recognized as one of crucial measures in battle against COVID-19, contributing to both the reduction of its negative impact on infected person and overall spread reduction. In this paper, we focus on adoption of model-driven approach to proactive and cost-effective vaccine distribution, relying on deep-learning (for vaccine-demand predictions) and multi-objective optimization (for solving the allocation problem). As outcome, software simulation tool for efficient vaccination planning, relying on the proposed approach is presented, showing promising results. Furthermore, the adoption of model-driven approach reduces both the learning curve and time necessary for experimentation.

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