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
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.
Optimising progress towards elimination of malaria. The project aims to advance mathematical knowledge by developing novel tools appropriate for modelling disease elimination. We will apply these new mathematical tools to the significant problem of malaria elimination in Vietnam. The expected outcomes are new tools for modelling disease elimination on a fine spatial resolution with heterogeneities in individual patient characteristics, calibrating models to household level data on disease transm ....Optimising progress towards elimination of malaria. The project aims to advance mathematical knowledge by developing novel tools appropriate for modelling disease elimination. We will apply these new mathematical tools to the significant problem of malaria elimination in Vietnam. The expected outcomes are new tools for modelling disease elimination on a fine spatial resolution with heterogeneities in individual patient characteristics, calibrating models to household level data on disease transmission and designing intervention strategies for maximum effect on disease transmission. The innovative combination of modelling, inference and optimisation ensures that the mathematical methods developed will be broadly applicable to modelling elimination strategies for other infectious diseases.
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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.