13. Description of the core message of your event and key topics to be covered (c.100 words):
The recent outbreaks of Foot-and-Mouth disease (FMD) in 2001 and 2007 and the global pandemic of H1N1 in 2009 have raised awareness of the potentially devastating effects to both livestock and humans of infectious disease epidemics.
To ensure an effective response, a good understanding of optimal control measures for different infectious diseases and epidemic scenarios is needed. Usually scientists approach such problems by performing experiments; however field experiments for infectious diseases are impractical and mathematical models are used to predict large-scale epidemic behaviour from a detailed understanding of local (e.g. farm/household) level or individual host level properties.
In this presentation I will focus upon the role that mathematics can play in providing predictions of optimal intervention strategies to control future outbreaks of disease. Basic SIR (Susceptible-Infected-Recovered) models of disease spread will be demonstrated by “simulating” a disease spreading through the audience.
I will then focus on high profile epidemics that I have studied in my own research – in particular foot-and-mouth disease, highly pathogenic avian influenza and H1N1. Audience members will be invited to run simulations via a computer that will show the effect of various strategies (vaccination, quarantine, culling etc.) in eradicating the disease.
Many public-health and veterinary agencies are increasingly relying on mathematical modellers to advise regarding optimal control policies to combat large scale epidemic. The power of mathematical models is such that they are still useful as predictive tools even in the presence of uncertainty. Climate models have long been able to accurately predict weather patterns in the presence of huge uncertainty in behaviour and I will highlight how epidemic models can similarly predict epidemic behaviour and optimal control strategies.