Development of a hybrid simulation model for hospital capacity in health emergencies

Simulating a hospital when a pandemic is faced is a complex task due to the healthcare system’s dynamic and multifaceted nature. This study proposes a hybrid model based on three models. A discrete-event model simulates hospital capacity and patient flow in the COVID-19 department. An agent-based model simulates the behaviour of healthcare personnel and their likelihood of infection, and analyzes the progression of the disease and its effects on the COVID-19 department. A system dynamics model estimates the infected population and its impact on hospital capacity. The model was validated and compared with historical data from a hospital in México. This hybrid approach enables hospital managers to gain a comprehensive view, capture interactions at multiple levels, identify behavioural patterns, achieve accurate and realistic outcomes, optimise resources, and consequently improve decision-making processes and generate more efficient policies for patient management during pandemics.