Project Abstract

Epidemiological modelling can be a powerful tool in recreating and analysing disease spread, helping to inform health policy both in the moment and retrospectively. One approach, compartmental models, represents a population in a series of differential equations. These models become increasing complex when more detail and thus accuracy is added. This Project researched, designed, and then implemented and analysed an epidemiological modelling program to represent all this information irrespective of an individual?��s mathematical background, allowing anyone to gain an understanding of the mechanics that drives disease spread. The final program allows for up to 4 charts to be simulated each with their own set of details and parameters, with steps taken to ensure the accessibility of the program. This, opening up knowledge of epidemiology to a wider audience. Improvements that can be made to the program including both stochastic and agent-based approaches are then discussed and researched.

Keywords: Epidemiology, Modelling, Python

 Conference Details

Session: Poster Session B at Poster Stand 88

Location: Sir Stanley Clarke Auditorium at Wednesday 8th 09:00 – 12:30

Markers: Mark Jones, Troy Astarte

Course: BSc Computer Science, 3rd Year

Future Plans: I’m continuing studies