An optimization model with simulation for optimal regional allocation of COVID-19 vaccines

Abstract

In response to the coronavirus disease 2019 (COVID-19) pandemic, the allocation of vaccines has become a crucial undertaking, particularly in the Philippines. The efficient distribution of vaccines across different regions remains vital. In this study, we present an approach to determine the optimal allocation of COVID-19 vaccines in the Philippines, leveraging actual data on the supply of vaccines per region for different brands. A notable advantage of our work, compared to existing models, is the comprehensive consideration of crucial factors, including vaccine effectiveness, waning immunity, various age groups, population data, and weekly vaccination rates. We formulate a linear programming model with the objective of minimizing both the primary and breakthrough infections. Several constraints are incorporated into the model, including vaccine supply, the size of the eligible population, weekly vaccination rates, and the interval between vaccine doses set by the Philippine government. Our findings show that prioritizing the pediatric population (aged 5 to 11) for the primary vaccination series within the initial three months is vital. Administering first booster shots to those aged 12 and older during this period is also recommended. Numerical results indicate a preference for highly effective vaccine brands in regions with a high COVID-19 incidence proportion. Conversely, vaccines with lower effectiveness are suitable for primary doses in regions with low COVID-19 cases. This research provides an analytical approach in addressing the complexities of COVID-19 vaccine distribution and allocation. It offers essential guidance to policymakers in the Philippines, enhancing population protection, and contributing to economic recovery.

Keywords

• Mathematical optimization model
• COVID-19 vaccines
• Regional vaccination scheduling
• Numerical simulation
• Linear programming
• Healthcare analytics