24 March 2021
Online Webinar - 16.00 – 17.00 GMT
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.
Faculty of Medicine, School of Public Health, Imperial College London
Prof Ferguson is part of UK's Imperial College COVID-19 Response Team. His research aims to improve understanding of the epidemiological factors and population processes shaping infectious disease spread in human and animal populations. A key practical focus is the analysis and optimisation of intervention strategies aimed at reducing transmission or disease burden. Much of his work is applied, informing disease control policy-making by public and global health institutions.
Tel: +44 (0)20 7598 1561