This research focuses on why some pathogens are particularly likely to jump between species and spread, and uses metagenomic technology to discover novel viruses and determine the possible microbial cause of disease syndromes (e.g. emerging tick-borne disease in Australia).

The data generated will be used to reveal some of the fundamental roles of virus ecology and evolution, and understand the measurable impact of the novel infections on public and animal health.

Professor Eddie Holmes is also using 'ancient DNA' to investigate the causes and patterns of spread of past pandemics such as plague and cholera.

This research uses modern genomics technologies to explore the diversity and evolution of microbial pathogens, especially viruses and bacteria of public health significance.

They look at how microbial pathogens evolve within an individual infection to generate a within-host microcosm of closely related bacteria/viruses, some of which can then be transmitted onward to a new host.

Each element of this process involves a complex interplay between competing pathogens or variants in the original host, immune pressure from both the infector and the newly infected individual, and a stochastic element of 'drift', or luck in making it through the bottleneck of transmission and into a new host.

Computational microbiology applies modern genomics technologies to study how pathogens interact, evolve and affect their human hosts, and how we can use this knowledge to improve healthcare and disease control.

Modelling diverse impacts of a major crisis, such as the COVID-19 pandemic, across multiple scales ranging from microbiology to epidemiology to social dynamics quickly becomes intractable.

A significant problem is the presence of feedback loops, with interventions and changes in social behaviour putting an evolutionary pressure on pathogens and causing the emergence of potentially even more transmissible variants.

We approach these challenges by combining (i) stochastic agent-based models which provide robust tools for tracing fine-grained effects of complex scenarios and intervention strategies with (ii) methods of socio-physics that capture multiscale feedback dynamics.

The Infectious Diseases, Immunisation and Emergencies (IDIE) research group is dedicated to advancing knowledge and understanding of infectious diseases transmission, prevention and control using epidemiology and population health approaches.

They apply a health systems lens to infectious diseases prevention and control and, conduct rigorous research, education, and training across the Asia-Pacific region. They develop innovative solutions to strengthen immunisation programs, disease surveillance, and emergency (e.g. outbreaks) preparedness and responses.