A Scalable Forecasting Framework to Predict COVID-19 Hospital Bed Occupancy
Jakob Heins, Jan Schoenfelder, Steffen Heider, Axel R. Heller, Jens O. Brunner
Abstract
We present a scalable forecasting framework with a Monte Carlo simulation to forecast the short-term bed occupancy of patients with confirmed and suspected COVID-19 in intensive care units and regular wards. Our forecasts were a central part of the official weekly reports of the Bavarian State Ministry of Health and Care from May 2020 to March 2021.
Topics & Concepts
OccupancyCoronavirus disease 2019 (COVID-19)Christian ministryScalabilityMonte Carlo method2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Intensive careComputer scienceEconometricsEmergency medicineStatisticsMedicineEngineeringIntensive care medicineVirologyEconomicsMathematicsPolitical scienceInternal medicineDatabaseOutbreakInfectious disease (medical specialty)DiseaseArchitectural engineeringLawCOVID-19 epidemiological studiesHealthcare Operations and Scheduling Optimizationdemographic modeling and climate adaptation