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  • Funded Activity

    Discovery Projects - Grant ID: DP0773987

    Funder
    Australian Research Council
    Funding Amount
    $339,000.00
    Summary
    Who acquires infection from whom across international borders? New approaches for control of emerging infections through understanding travel patterns. Mathematical modelling of data on travellers traversing Australia's borders and their contact patterns can be used to understand the pathways by which infectious diseases enter and spread in Australia. Currently available social contact data which informs models are inadequate and outdated. Gathering new data relevant to modern society will help .... Who acquires infection from whom across international borders? New approaches for control of emerging infections through understanding travel patterns. Mathematical modelling of data on travellers traversing Australia's borders and their contact patterns can be used to understand the pathways by which infectious diseases enter and spread in Australia. Currently available social contact data which informs models are inadequate and outdated. Gathering new data relevant to modern society will help control future infectious disease threats to our society. Our aim is to collect detailed, unique data on demography, behavioural and social patterns of travellers and residents, and use this to develop mathematical models to evaluate effective control measures for emerging infections in Australia. This study will make a unique contribution to national disease control policy.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558357

    Funder
    Australian Research Council
    Funding Amount
    $202,318.00
    Summary
    New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release o .... New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release of an infectious disease such as smallpox. The project will enhance preparedness through a better understanding of the relative merits of different control strategies, and provide new methodology that can dynamically guide border and outbreak control in the midst of an outbreak by making effective use of data.
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    Funded Activity

    Discovery Projects - Grant ID: DP0664624

    Funder
    Australian Research Council
    Funding Amount
    $246,000.00
    Summary
    New Directions in Non-linear Mathematical Asymptotics. Major challenges such as predicting epidemics or modelling cancer rely on our understanding of simple mathematical models with extremely complicated solutions. The first and only model in the literature to reproduce the three-phase cycle of immune response in HIV/AIDS was based on cellular automata. Its results are extremely sensitive to infinitesimally small changes in parameters. Yet, no technique exists to study such variation in cellular .... New Directions in Non-linear Mathematical Asymptotics. Major challenges such as predicting epidemics or modelling cancer rely on our understanding of simple mathematical models with extremely complicated solutions. The first and only model in the literature to reproduce the three-phase cycle of immune response in HIV/AIDS was based on cellular automata. Its results are extremely sensitive to infinitesimally small changes in parameters. Yet, no technique exists to study such variation in cellular automata. This research will provide new methods for prediction and analysis of such models.
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    Funded Activity

    Linkage Projects - Grant ID: LP100100242

    Funder
    Australian Research Council
    Funding Amount
    $360,000.00
    Summary
    Can an anti-HIV gene in blood stem cells protect from immune depletion by HIV? Approximately 15,000 individuals in Australia are currently HIV infected. Gene therapy has the capacity to remove antiretroviral treatment related issues, dramatically decrease treatment costs and simplify treatment of HIV. In this study we will model a new approach to treat HIV in which the patient's own cells are used as the therapy by incorporating an anti-HIV gene. These cells are then re-introduced into the p .... Can an anti-HIV gene in blood stem cells protect from immune depletion by HIV? Approximately 15,000 individuals in Australia are currently HIV infected. Gene therapy has the capacity to remove antiretroviral treatment related issues, dramatically decrease treatment costs and simplify treatment of HIV. In this study we will model a new approach to treat HIV in which the patient's own cells are used as the therapy by incorporating an anti-HIV gene. These cells are then re-introduced into the patient. The strong mathematical focus of this project, and its application to a promising approach against HIV, will place Australia at the forefront of the mathematics of gene research and contribute to the National Priority Area of Promoting and Maintaining Good Health and the Priority Goal of Preventative Healthcare.
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    Funded Activity

    Discovery Projects - Grant ID: DP0558199

    Funder
    Australian Research Council
    Funding Amount
    $348,000.00
    Summary
    Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give ins .... Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give insight by carefully quantifying and modelling uncertainty for such topics as the transmission rate of infectious diseases, the spatial distribution of plant and animal species, investigating biological theory for the genome of a virus, and changes in human fertility.
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