Frank Ball.
Frank Ball. Photo: EAJ 2016.

Epidemiology models have been studied for several hundred years, but mathematical analysis of the spread of infectious diseases faces many difficulties that are not present in the statistical analysis of other diseases. These additional modelling complications are due to the fact that the process of becoming infected involves interactions with other individuals, as well as the fact that the exact time of infection and the infectious period are rarely observed.

To obtain realistic results, models need to accommodate the changing attributes of a population over time: its size can increase or decrease, some people will die, others will be born, and it can split into several isolated groups. Changing behaviours also need to be a part of the model, since people can form new connections and end previous ones. People can also change their social behaviour when they discover infected people around them. Extending the present models to allow for such flexibility of assumptions is mathematically very challenging, reaching far beyond the existing theory. Frank Ball is a world-leading expert on stochastic models of epidemics and has already an established collaboration with Professor Tom Britton and a research group at Stockholm University.

The extended knowledge on how epidemics evolve will hopefully contribute to improved health policy. The goal is to find ways in which society can prevent outbreaks of epidemics, for example, by changing the behaviour of those who are infected, or to calculate the minimum number of people that need to be vaccinated to prevent an epidemic outbreak.