Frank Ball

Program for mathematics 2017

Visting Professor

Frank Ball
Professor at the University of Nottingham, UK

Nominated by:
Stockholm University

Developing better epidemiology models 

Frank Ball is currently professor at the University of Nottingham, UK. Thanks to a grant from the Knut and Alice Wallenberg Foundation, he will be a visiting professor at the Department of Mathematics, Stockholm University, Sweden. 

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 modeling complications are because the process of becoming infected involves interactions with other individuals, as well as because 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 behaviors also need to be modeled, as people can form new connections and end previous ones. People can also change their social behavior 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 statistical epidemiology and has already an established collaboration with professor Tom Britton and the research group at Stockholm University. 

The expected results are not only of interest to researchers. The hope is that extending the knowledge of how the epidemics evolve will contribute to improved health policy. The goal is to find ways in which society can prevent outbreaks of epidemics, for example, by changing the behavior of those who are infected, or to calculate the minimum number of infected people necessary for an infection to take hold in an isolated group.