AI for epidemic modelling: Nature 2025 and tool development
I recently contributed to Nature (2025) on artificial intelligence for infectious disease epidemic modelling. The paper reviews how modern AI methods can support epidemic forecasting, surveillance, intervention planning, and model acceleration while still needing careful public-health interpretation.
- Paper: https://doi.org/10.1038/s41586-024-08564-w
- Related tool: emidm
- Related research section: AI-enabled epidemic modelling
Alongside this, my group continues work on emulator-based approaches that improve calibration speed and scenario exploration for policy-facing analyses. The aim is practical: make complex infectious disease models easier to interrogate under uncertainty, without losing sight of the assumptions that make those models useful.