Sandor Beregi (Imperial College London)

Speaker: Sandor Beregi (Imperial College London)

Title: Model-Predictive Optimisation of Epidemic Response Policy and Interaction with Population Behaviour

Abstract:
When and how should we intervene to manage an emerging infectious disease most effectively? Deciding when to enforce or relax non-pharmaceutical interventions (NPIs) based on real-time outbreak surveillance data is a central challenge in infectious disease epidemiology. Practical surveillance data, often characterised by reporting delays and infection under-ascertainment, can misinform decision-making. This may lead to mistimed NPIs that fail to control disease spread or allow harmful epidemic peaks that overwhelm healthcare capacities.
In this talk, I will introduce EpiControl, a novel model-predictive control algorithm designed to optimise NPI decisions by jointly minimising cumulative future risks and costs across stochastic epidemic projections. I will demonstrate how this algorithm outperforms data-insensitive strategies while also exploring the intrinsic limitations of surveillance quality, disease growth rates, and decision frequency in flattening epidemic peaks or reducing endemic oscillations. Additionally, I will present my ongoing research on integrating population behaviour into the policy-making framework.