Systems Modelling and SimulationSystems Modelling and Simulation is a discipline that relies on creating a suitable computerised representation (Computer Model) of a system, with all or a subset of its properties, which is then iteratively executed over time (Simulated) to study the behaviour of the system, with the aim to better understand the interaction of its parts, as well as the whole. Systems Modelling and Simulation techniques are widely used in fields as varied as engineering, computer science, physics, chemistry, biology, economics and medicine. Advances in Systems Engineering, Software Engineering and computational platforms have enabled the real-time or near real-time modelling and simulation of complex systems for optimisation, prediction and what-if analyses.

We are using mathematical modelling and computer simulation to study patient journeys across an entire integrated care pathway, from the management of health in the home to acute care and specialist services. Models of disease trajectories and discrete event simulation of care pathways are combined to generate stochastic modelling of patient journeys, in order to study and explore possible ways of improving patient and clinician experience, as well as outcomes.

Our particular emphasis is on patient groups with complex care needs. Since the complexity of the care pathways presented by these patient groups is related to an intricate and interlinked set of psycho-social issues, lifestyle factors and provision of care between multiple separate health care providers and multidisciplinary teams (MDT), we aim to model the entire integrated care pathway, simulating patient behaviour and identifying possible opportunities for improved delivery of care and improved MDT training.


Current projects

Current projects


Previous projects

Previous projects

General Enquiries


For further information on our research projects or current opportunities, please contact:

Professor of Surgical Computing and Simulation Science
Professor Fernando Bello

f.bello@imperial.ac.uk
+44 (0)20 3315 8231