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Research Topic : Predictive Modelling
Field of Research : Epidemiology
Australian State/Territory : NSW
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  • Funded Activity

    Discovery Projects - Grant ID: DP0880013

    Funder
    Australian Research Council
    Funding Amount
    $216,000.00
    Summary
    Modelling and estimation techniques for the transmission and control of Tuberculosis with new and existing vaccines. Most Tuberculosis in Australia is seen in foreign-born people. Australia has an important role in providing leadership in the Asia-Pacific region in Tuberculosis control, which will have flow-on benefits to TB control in this country. Using mathematical models, this project will assess the use of vaccines for Tuberculosis in the developing world. Rising levels of extremely drug r .... Modelling and estimation techniques for the transmission and control of Tuberculosis with new and existing vaccines. Most Tuberculosis in Australia is seen in foreign-born people. Australia has an important role in providing leadership in the Asia-Pacific region in Tuberculosis control, which will have flow-on benefits to TB control in this country. Using mathematical models, this project will assess the use of vaccines for Tuberculosis in the developing world. Rising levels of extremely drug resistant infections make this a timely and important study with significant policy implications, both externally and in the Australian context.
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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 Currently available social contact data which informs models are inadequate and outdated.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: DP160102742

    Funder
    Australian Research Council
    Funding Amount
    $510,000.00
    Summary
    Large-scale computational modelling of epidemics in Australia. The project aims to develop novel computational epidemiological models to contribute to guidelines for optimal prophylaxis, vaccination and case management. Emerging threats posed by infectious diseases and bioterrorism could have dramatic effects on the Australian population, productivity and economy. The project aims to improve the accuracy and scope of modern computational epidemiological models by integrating large-scale Census d .... Large-scale computational modelling of epidemics in Australia. The project aims to develop novel computational epidemiological models to contribute to guidelines for optimal prophylaxis, vaccination and case management. Emerging threats posed by infectious diseases and bioterrorism could have dramatic effects on the Australian population, productivity and economy. The project aims to improve the accuracy and scope of modern computational epidemiological models by integrating large-scale Census datasets and explicitly simulating the entire population down to the level of single individuals, coupled with complex network-based and information flow analysis. The intended outcomes include a more precise and efficient forecasting of critical epidemic dynamics, and increased effectiveness of prevention, mitigation and management of socio-economic, socio-ecological and national security crises.
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