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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.
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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Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and r ....Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and recovery rates are such that the basic reproduction number of the disease is near the critical value 1. The project will plan to both analyse particular epidemic models and develop new methodologies applicable in broader contexts. The mathematical predictions will be tested through simulations and comparison to real-world data. The significant outcome of the project should be the advancement in mathematical understanding of infectious disease spread, eventually leading to improved epidemic surveillance and control, and resulting in more effective protection of public health, improved quality of life, and obvious economic benefits.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101127
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
An integrated statistical genetics framework for breeding superior wheat varieties. Genetic studies in agriculture are rapidly increasing in size and complexity in pursuit of genes behind desirable traits such as yield and water use efficiency. This project will address the need for efficient statistical methods to analyse genetic data and thus enable production of wheat varieties that will contribute to Australian food security.
Quantifying complexity and measuring structure within complex systems. Most interesting systems are complex. The complex systems of interest in this project are characterised by a simple dynamical behaviour on each individual part; and a complicated web of interaction between the many distinct parts. The project will focus on the massive system of interacting neurones in the brain, and transmission of influenza via interpersonal contacts. This project will provide a better model of that web of i ....Quantifying complexity and measuring structure within complex systems. Most interesting systems are complex. The complex systems of interest in this project are characterised by a simple dynamical behaviour on each individual part; and a complicated web of interaction between the many distinct parts. The project will focus on the massive system of interacting neurones in the brain, and transmission of influenza via interpersonal contacts. This project will provide a better model of that web of interactions; and new methods for statistically validating this model against data. Existing models of complex networks are statistically biased so, by employing robust statistical methodologies, this problem will be rectified and provide a method for randomly choosing representative complex systems. Read moreRead less