Population-scale agent-based modelling for epidemic response and public health policy
Population-scale agent-based modelling for epidemic response and public health policy
Name of applicant
Mark Khurana
Title
Postdoctoral Fellow
Institution
Imperial College London
Amount
DKK 2,734,003
Year
2026
Type of grant
Internationalisation Fellowships
What?
This project will develop a national simulation tool for infectious disease outbreaks. Rather than assuming everyone behaves the same way, it will model individuals and their interactions, accounting for differences in age, health, income, and household structure. The result is a tool that lets us test policy scenarios virtually, enabling smarter planning for future epidemics.
Why?
When governments face an outbreak, they must make rapid decisions under uncertainty and rarely have the full picture. Conventional models struggle to capture the complexity of how diseases spread across diverse populations, leaving critical questions unanswered. Better simulation tools can fill that gap, helping policymakers anticipate the effects of different interventions and respond more effectively.
How?
The project will combine genetic information from viruses with health and sociodemographic data from Denmark to train a large-scale simulation model. An AI-powered interface will then let public health professionals test scenarios such as earlier interventions, targeted testing strategies, or faster vaccine rollout, and explore their likely outcomes without needing technical expertise.