Analyzing the Impact of Vaccination on COVID-19 Spread and Hospitalizations: A Multi-Paradigm Simulation Modeling Approach

Abstract

Multi-paradigm simulation modeling aids the study and analysis of complex systems and their internal interactions. Given the inherent variability that exists in real-world settings, the use of different structures and methods is necessary to accurately represent the system under study. This study integrates Discrete Event Simulation and Agent-Based Modeling, developing a multi-paradigm simulation model to study the emergent COVID-19 crisis. In specific, the goal of this research is to determine how the vaccine distribution affects the spread of COVID-19 as well as hospitalizations for the state of Alabama. The simulation model incorporates three main components, including the supply chain of vaccines, the spread of COVID-19, and hospitalizations. The supply chain of vaccines simulation component studies the availability of trucks for supplying the vaccines and vaccine damage due to inappropriate handling and storage. The spread of the COVID-19 component incorporates the Susceptible Exposed Infected Recovery epidemic model. Lastly, the hospitalizations component considers capacity requirements (in terms of the number of available beds) and treatment times. The multi-paradigm model enables a better understanding of the interactions between variables of interest, helps to evaluate hospital bed requirements, and provides metrics that support the management and control of the epidemic and healthcare system.