With recent advances in data availability (both epidemiological and molecular) and affordable high-performance computing, mathematical models of infectious disease spread now offer the potential to provide predictive, quantitative analyses of alternative disease control and treatment strategies, as well as qualitative insight into the complex non-linear processes shaping pathogen replication and evolution.

An important strand of Prof Ferguson’s research program is to develop the statistical and mathematical tools necessary for such increasingly sophisticated models to be rigorously tested and validated against epidemiological, molecular and experimental data. 

The breadth of his research interests reflects his belief that comparative analyses of different host-pathogen systems can provide powerful insights into the population processes common to many infectious diseases, while highlighting how key differences in disease biology, route of transmission or host population structure determine observed differences in patterns of infection.