Real-time modelling for forecasts during infectious disease outbreaks

Forecasts based on computer models using data collected in real time are now used throughout society from weather reports to air-traffic control. Real-time forecasts during infectious disease outbreaks have the potential to inform the public health response to the outbreak. 

I aim to understand how mathematical models can generate accurate forecasts, and use this to develop methods and software that can be used routinely during disease outbreaks. I will use the latest methods for Bayesian inference on past and current infectious disease outbreaks to determine how to produce the most accurate forecasts. I will also study how the quality of forecasts affects public health decisions and how this can be used to assess the reliability of recommendations that are based on forecasts. I will also identify gaps in data collection and work out what additional information would lead to better forecasts.    

My findings could lead to improvements in forecasts made during outbreaks of infectious disease.