Discovery Early Career Researcher Award - Grant ID: DE220100663
Funder
Australian Research Council
Funding Amount
$440,850.00
Summary
The Real Price of Health: Experiences of Out-of-Pocket Costs in Australia. This project aims to investigate the experiences and preferences of Australian families and individuals on low, middle, and high incomes in managing the out-of-pocket costs of chronic disease. This project aspires to ensure outcomes that are relevant to the public and patients through involving people living with chronic disease in the research team. The project expects to generate a discrete choice model that describes p ....The Real Price of Health: Experiences of Out-of-Pocket Costs in Australia. This project aims to investigate the experiences and preferences of Australian families and individuals on low, middle, and high incomes in managing the out-of-pocket costs of chronic disease. This project aspires to ensure outcomes that are relevant to the public and patients through involving people living with chronic disease in the research team. The project expects to generate a discrete choice model that describes people with chronic diseases’ preferences, and the trade-offs that they are faced with when deciding how to manage out-of-pocket health costs. The evidence arising from this innovative study will be used to directly inform Australian health policy, leading to wide-ranging health and economic benefits for the whole community.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101570
Funder
Australian Research Council
Funding Amount
$363,128.00
Summary
Getting real about risk: using medical records in the geospatial analysis of chronic disease risk in Australia. Crafting an informed response to the alarming rise of chronic disease is the most challenging public health issue in Australia. This project will design a method of producing fine-grained maps of future chronic disease risk directly from the medical records held in general practices. This will involve innovative new techniques in data handling, geocoding, analysis and interpolation to ....Getting real about risk: using medical records in the geospatial analysis of chronic disease risk in Australia. Crafting an informed response to the alarming rise of chronic disease is the most challenging public health issue in Australia. This project will design a method of producing fine-grained maps of future chronic disease risk directly from the medical records held in general practices. This will involve innovative new techniques in data handling, geocoding, analysis and interpolation to create risk surfaces across a metropolitan area and comparisons with built environment and socio-economic data, providing new insights into risk factors. It will be the first such geospatial analysis of real clinical data in Australia, which will pioneer geospatial risk analysis for planning preventative health measures, interventions and policy responses.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE140101886
Funder
Australian Research Council
Funding Amount
$386,929.00
Summary
Plant microRNA targeting: defining regulatory factors additional to complementarity. Central to our understanding of microRNA biology is the identification of which genes they target. In plants, high complementarity is regarded as the sole determinant, and drives bioinformatic predictions. However, functional evidence is inconsistent with this, arguing that complementarity alone is insufficient to accurately predict targets. This project uses novel applications of next generation sequencing to c ....Plant microRNA targeting: defining regulatory factors additional to complementarity. Central to our understanding of microRNA biology is the identification of which genes they target. In plants, high complementarity is regarded as the sole determinant, and drives bioinformatic predictions. However, functional evidence is inconsistent with this, arguing that complementarity alone is insufficient to accurately predict targets. This project uses novel applications of next generation sequencing to categorise bioinformatically predicted Arabidopsis targets as either strongly or poorly regulated. These categories will be analysed to determine what factors, in addition to complementarity, are required for strong targeting. The outcomes will impact artificial microRNA design and have important implications for biotechnology. Read moreRead less