Hospital preparedness in epidemics by using simulation. The case of COVID-19

Abstract

AbstractThis paper presents a discrete event simulation model to support the decision-making concerned with the short-term planning of the necessary hospital resources, especially Intensive Care Unit (ICU) beds, to face outbreaks, as the SARS-CoV-2. Being used as a short-term forecasting tool, the simulation model requires an accurate representation of the current system state and high fidelity in mimicking the system dynamics from that state. The two main components of the simulation model are the stochastic modeling of the admission of new patients and the patient flow through the hospital facilities. For the patient arrival process, we analyze different models based on growth curves of the twenty most affected countries (until June 15) and propose the use of the Gompertz curve. The length of stay is divided into several stages, each one modeled separately. We analyze the starting of the simulation model, which requires different procedures depending on the information available about the patients currently hospitalized. We also report the use of this simulation model during the COVID-19 outbreak in the Autonomous Community of Navarre, in Spain. Every day, the research team informed the regional logistic team in charge of planning the health resources, who programmed the ward and ICU beds based on the resulting predictions.