Click here to flash read.
arXiv:2403.07971v1 Announce Type: new
Abstract: 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 \ac{VH} on disease dynamics, including the expected number of hospitalizations and fatalities. We propose improvements to the \ac{SEIR} model for COVID-19 by incorporating the influence of vaccination, \ac{VH}, and resource availability on the disease dynamics. We collect publicly available data and perform data analysis to capture \ac{VH} dynamic changes over time and develop scenario paths for \ac{VH}. We simulate the proposed compartmental model for each \ac{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 \ac{VH} improves health outcomes, reinforcing the importance of addressing \ac{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.
No creative common's license