Understanding mutation and genetic reassortment in viruses: new mathematical models of viral dynamics and evolution. This project aims to understand how evolutionary processes and ecological conditions combine to ignite and sustain viral epidemics. Using novel mathematical models and statistical methods we will study the manner in which viral genes mutate and are recombined, as well as the rates of these important forces.
Microbial natural history and molecular evolution. This project aims to develop mathematical and computational models of microbial evolution that capture dynamics at both within-host and between-host scales, combined with processes of mutation. Integration of these elements with computational statistical methods will produce a framework that will enable inference from genome sequencing data. The mathematical models will be applied to bacterial genomic data to investigate how natural selection ac ....Microbial natural history and molecular evolution. This project aims to develop mathematical and computational models of microbial evolution that capture dynamics at both within-host and between-host scales, combined with processes of mutation. Integration of these elements with computational statistical methods will produce a framework that will enable inference from genome sequencing data. The mathematical models will be applied to bacterial genomic data to investigate how natural selection acts on experimental and natural populations of microorganisms. The mathematical models and statistical approaches developed here are intended to be applicable to infectious disease of both humans and domesticated animals, and could influence public health policies.Read moreRead less
New methods for integrating population structure and stochasticity into models of disease dynamics. Epidemics, such as the 2007 equine 'flu outbreak and 2009 swine 'flu pandemic, highlight the need to make informed decisive responses. This project will develop new methods that incorporate two important aspects of disease dynamics---host structure and chance---into mathematical models, and determine their impact in terms of controlling infections.
Developing mathematical models of infection and transmission to link biology, epidemiology and public health policy. Infectious diseases constitute a significant burden on the health of the population. Understanding how best to control them requires a multi-faceted approach, combining data from biology, medicine and population health with mathematical and computational models of disease transmission. This project will investigate the "flu" and other diseases.
Discovery Early Career Researcher Award - Grant ID: DE120101529
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Transmission dynamics modelling of zoonotic neglected tropical diseases. This project will develop mathematical models to simulate zoonotic disease transmission and control. Results will provide novel insight for policy makers into effective interventions for schistosomiasis, echinococcosis and clonorchiasis, as well as provide a methodological platform for adaptation to other zoonotic emerging and re-emerging diseases.
Australian Laureate Fellowships - Grant ID: FL100100183
Funder
Australian Research Council
Funding Amount
$2,168,370.00
Summary
Biological adaptation under natural and anthropogenic conditions. This project covers all four national priority areas. Nature abounds with conflicts between what is good for the individual or a larger entity (a population, a society, or a species). Researching them will explain why populations adapt or fail to adapt to novel conditions (e.g., climate change) and predict when interventions are beneficial. Similar rules govern the spread of invasive species. Even health problems, e.g., new virule ....Biological adaptation under natural and anthropogenic conditions. This project covers all four national priority areas. Nature abounds with conflicts between what is good for the individual or a larger entity (a population, a society, or a species). Researching them will explain why populations adapt or fail to adapt to novel conditions (e.g., climate change) and predict when interventions are beneficial. Similar rules govern the spread of invasive species. Even health problems, e.g., new virulent strains of human, animal or plant diseases, require such evolutionary thinking. Cutting-edge mathematical tools also prepare Australians for an era in the near future where genomic data are so cheap to acquire that training in complex mathematical and logical analysis becomes a factor limiting scientific progress.Read moreRead less