Shameless plug alert: Win prizes by forecasting real healthcare data to help UK’s health service save lives
Statistical Modeling, Causal Inference, and Social Science 2026-04-01
This post is by Lizzie, on behalf of my colleague Will Pearse in the UK about a cool forecasting competition. It’s different in some ways than the cherry competition, but the same in other ways, predicts blooms, predict beds… Only predict! (Only connect!)
Every four hours of delay in admitting patients from an emergency department adds up to roughly 25 potentially avoidable deaths per month (Howlett et al. 2026). We’re running a contest where you can forecast those risks 1–10 days ahead so UK hospitals can take action.
The data in the contest are all real healthcare data. The data come from the Bristol NHS system, with 220 variables ranging from daily counts to 15-minute feeds (e.g., bed occupancy, ambulance waiting times). You build a model in R or Python, submit by June 5, and forecasts are judged by mean squared error over short- and medium-term horizons.
The winning model(s) will be implemented in Bristol’s live system to flag emerging system pressure and so this is, literally, a chance for you to save lives with your stats know-how.
If you like this sort of thing (…and of course you do, you’re reading this blog…) then please sign up for the SPHERE-PPL mailing list. We (SPHERE-PPL) are organising a series of forecasting challenges just like this one, and we can tell you more about them.
GitHub repo to enter: https://github.com/SPHERE-PPL/NHS-EAD-forecast