Models of infectious disease transmission with complex pathogen and population characteristics

SPEAKER: Dr Nic Geard, IAS Vanguard Fellow, University of Melbourne

Infectious diseases impose a significant health and economic burden upon individuals and societies. Mathematical and computational modelling are increasingly used to understand how pathogens spread through populations, and to inform decisions about their control.

Traditional compartmental approaches to modelling infectious diseases, while powerful, often require simplifying assumptions about the characteristics of both pathogens and populations. However, reality is complex: pathogens with multiple strains present a challenge for vaccine design, and optimal use of healthcare resources requires interventions tailored to the characteristics of specific populations. Individual-based models can enable us to capture important aspects of pathogen and population complexity.

In this talk, I will describe our application of individual-based modelling to two policy-relevant challenges in infectious disease control. In the first, we developed a population model that incorporates realistic demographic structure and dynamics, and used it to evaluate the impact of maternal vaccination strategies against pertussis (whooping cough) in developed and developing country settings. In the second, we developed a novel multi-strain model of the bacterial pathogen Group A Streptococcus, which sheds new light on the relationship between within-host processes of infection and immunity and population-level epidemiology, and the necessary characteristics of an effective vaccine.

Dr Nic Geard is a Vanguard Fellow at the Institute of Advanced Studies at the University of Birmingham, and Senior Lecturer at the School of Computing and Information Systems, University of Melbourne, Australia. His IAS public lecture also forms part of the Artificial Intelligence and Natural Computation (AINC) seminar series in the School of Computer Science, UoB.

All students and staff are welcome to attend.