Evaluating the Impact of Vaccine Hesitancy on the Allocation of Vital Resources During COVID-19 Pandemic

The COVID-19 pandemic highlighted significant challenges in the allocation of vital healthcare resources. Existing epidemiological models, specifically compartmental models, aimed to predict the spread of the COVID-19 virus and its impact on the population, but they overlooked the influence of vaccine hesitancy (VH) on disease dynamics, including the expected number of hospitalizations and fatalities. We propose improvements to the susceptible-exposed-infectious-recovered (SEIR) model for COVID-19 by incorporating the influence of vaccination, VH, and resource availability on the disease dynamics. We collect publicly available data and perform data analysis to capture VH dynamic changes over time and develop scenario paths for VH. We simulate the proposed compartmental model for each VH path to explain the impacts of public attitudes toward vaccination, the impacts of healthcare resources on patient outcomes, and the timing of vaccination rollout on the progression and severity of the epidemic. Our analysis demonstrates that reducing VH improves health outcomes, reinforcing the importance of addressing VH to curb the spread of infectious diseases. Our results show that adequate levels of critical healthcare resources are crucial for minimizing fatalities and also highlight the life-saving impact of timely and effective vaccination programs.