biostudies-literatureUnknown9(2)Lafuente M<h4>Objective</h4>This study aims to build a multistate model and describe a predictive tool for estimating the daily number of intensive care unit (ICU) and hospital beds occupied by patients with coronavirus 2019 disease (COVID-19).<h4>Material and methods</h4>The estimation is based on the simulation of patient trajectories using a multistate model where the transition probabilities between states are estimated via competing risks and cure models. The input to the tool includes the dates of COVID-19 diagnosis, admission to hospital, admission to ICU, discharge from ICU and discharge from hospital or death of positive cases from a selected initial date to the current moment. Our tool is validated using 98,496 cases positive for severe acute respiratory coronavirus 2 extracted from the ArHeliyone13545https://www.ebi.ac.uk/biostudies/studies/S-EPMC9899510biostudies-literatureA multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19.PMC9899510Lafuente MLopez FJAsin JCebrian ACMateo PMBorque-Fernando AEsteban LMMoler JAPerez-Palomares ASanz GfalseA multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19.<h4>Objective</h4>This study aims to build a multistate model and describe a predictive tool for estimating the daily number of intensive care unit (ICU) and hospital beds occupied by patients with coronavirus 2019 disease (COVID-19).<h4>Material and methods</h4>The estimation is based on the simulation of patient trajectories using a multistate model where the transition probabilities between states are estimated via competing risks and cure models. The input to the tool includes the dates of COVID-19 diagnosis, admission to hospital, admission to ICU, discharge from ICU and discharge from hospital or death of positive cases from a selected initial date to the current moment. Our tool is validated using 98,496 cases positive for severe acute respiratory coronavirus 2 extracted from the Ar2023-01-01T00:00:00Z2023 Feb2025-04-21T22:09:57.285Z2024-11-20T06:38:55.719ZS-EPMC98995103677691410.1016/j.heliyon.2023.e13545