BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Philip Gerlee (Chalmers University of Technology & University of G othenburg) DTSTART:20250618T111500Z DTEND:20250618T120000Z DTSTAMP:20260422T155200Z UID:gbgstats/91 DESCRIPTION:Title: Evaluation of respiratory disease hospitalisation forecasts using synthe tic outbreak data\nby Philip Gerlee (Chalmers University of Technology & University of Gothenburg) as part of Gothenburg statistics seminar\n\nL ecture held in MVL14.\n\nAbstract\nForecasts of hospitalisations of infect ious diseases play an important role for allocating healthcare resources d uring epidemics and pandemics. Large-scale analysis of model forecasts dur ing the COVID-19 pandemic has shown that the model rank distribution with respect to accuracy is heterogeneous and that ensemble forecasts have the highest average accuracy. Building on that work we generated a maximally d iverse synthetic dataset of 324 different hospitalisation time-series that correspond to different disease characteristics and public health respons es. We evaluated forecasts from 14 component models and 6 different ensemb les. Our results show that component model accuracy was heterogeneous and varied depending on the current rate of disease transmission. Going from 7 day to 14 day forecasts mechanistic models improved in relative accuracy compared to statistical models. A novel adaptive ensemble method outperfor ms all other ensembles\, but is closely followed by a median ensemble. We also investigated the relationship between ensemble error and variability of component forecasts and show that the coefficient of variation is predi ctive of future error. Lastly\, we validated the results on data from the COVID-19 pandemic in Sweden. Our findings have the potential to improve ep idemic forecasting\, in particular the ability to assign confidence to ens emble forecasts at the time of prediction based on component forecast vari ability.\n LOCATION:https://researchseminars.org/talk/gbgstats/91/ END:VEVENT END:VCALENDAR