Mathematical and statistical methods for modelling invivo pathogen dynamics. This project aims to develop mathematical models and Bayesian statistical methods that better capture how natural defence responses and drugs help control infection. When viruses (e.g. influenza) or parasites (e.g. malaria) invade the human body, they begin to replicate. To date, only simple mathematical models have been developed to capture these processes, and these models are not well formulated. This project will im ....Mathematical and statistical methods for modelling invivo pathogen dynamics. This project aims to develop mathematical models and Bayesian statistical methods that better capture how natural defence responses and drugs help control infection. When viruses (e.g. influenza) or parasites (e.g. malaria) invade the human body, they begin to replicate. To date, only simple mathematical models have been developed to capture these processes, and these models are not well formulated. This project will improve biomathematics and biostatistical algorithms for pathogen dynamics and is ultimately expected to benefit public health and clinical research aimed at alleviating the effect of infectious diseases on human health.Read moreRead less
Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable mode ....Statistical methods for quantifying variation in spatiotemporal areal data. This project aims to develop new statistical methods for extracting insights into spatial and temporal variation in areal data. These tools will extend the Australian Cancer Atlas which provides small area estimates for 20 cancers across Australia. The project is significant because it will allow government and other organisations to reap dividends from investment in collecting spatial information and it will enable modelled small-area estimates to be released without compromising confidentiality. The expected outcomes include new statistical knowledge and new insights into cancer. The results will benefit the many disciplines, managers and policy makers that make decisions based on geographic data mapped over space and time. Read moreRead less
Enhancing Aspects Of Time-to-event Analysis Methodology In Randomised Trials
Funder
National Health and Medical Research Council
Funding Amount
$548,446.00
Summary
Time-to-event analysis is a statistical method for examining the occurrence of disease-related events in individuals followed for varying periods of time. The method is widely used in health research. The technicalities of the methods are subtle and by paying careful attention to these this grant will provide extended methods, new software, and apply methods more effectively to gain new insights to disease progress, and to enhance the efficiency of health research.
Nowcasting outbreaks leveraging genomic and epidemiological data. This project aims to inform outbreak response planning by developing new models of infectious disease outbreaks. The project expects to generate new knowledge on the processes driving ongoing outbreaks including those of the novel coronavirus (COVID-19) and African swine fever by integrating the latest advances in Bayesian outbreak inference alongside unique simulation approaches. Expected outcomes should include a shift in how mo ....Nowcasting outbreaks leveraging genomic and epidemiological data. This project aims to inform outbreak response planning by developing new models of infectious disease outbreaks. The project expects to generate new knowledge on the processes driving ongoing outbreaks including those of the novel coronavirus (COVID-19) and African swine fever by integrating the latest advances in Bayesian outbreak inference alongside unique simulation approaches. Expected outcomes should include a shift in how models are developed and used to inform the response to outbreaks as they unfold. This should enable more rapid outbreak containment in Australia and overseas, leading to reduced impacts on public and animal health, and associated industries.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE170100785
Funder
Australian Research Council
Funding Amount
$345,491.00
Summary
Mathematical and statistical modelling of antimalarial drug action. This project aims to develop a mathematical model to optimise global antimalarial treatment policy. Malaria-causing parasites are resistant to the most potent antimalarial drug available. If left unaddressed, a catastrophic rise in global malaria incidence and mortality could occur. Changes to global antimalarial treatment policy increasingly rely on mathematical models, but they do not encompass recent breakthroughs in antimala ....Mathematical and statistical modelling of antimalarial drug action. This project aims to develop a mathematical model to optimise global antimalarial treatment policy. Malaria-causing parasites are resistant to the most potent antimalarial drug available. If left unaddressed, a catastrophic rise in global malaria incidence and mortality could occur. Changes to global antimalarial treatment policy increasingly rely on mathematical models, but they do not encompass recent breakthroughs in antimalarial drug action and the immune response. This project’s model is expected to improve antimalarial drug dosing regimens and control the spread of antimalarial drug resistance.Read moreRead less
Integrating niches, interactions and dispersal in species distribution models. This proposal aims to develop a framework for statistical modelling that integrates across spatial scales and disentangles the processes of environmental tolerance, biotic interactions and dispersal. Understanding the processes that drive species distributions and ecological communities is central to ecology and environmental management. This knowledge can be used to anticipate the impacts of environmental change on e ....Integrating niches, interactions and dispersal in species distribution models. This proposal aims to develop a framework for statistical modelling that integrates across spatial scales and disentangles the processes of environmental tolerance, biotic interactions and dispersal. Understanding the processes that drive species distributions and ecological communities is central to ecology and environmental management. This knowledge can be used to anticipate the impacts of environmental change on ecosystems, and the likely benefits of interventions. Current statistical models limit the data that can be used and the ecological questions that can be answered. This project expects to improve our ability to predict species distributions under changed environments given interacting species and dispersal across the landscape.Read moreRead less
High Predictive Performance Models via Semi-Parametric Survival Regression. This project will develop novel statistical models for high prediction performance. When applied to help doctor to treat patients, these models allow the users to include gene or other biomarkers for predicting effectiveness of a treatment. When applied to risk management in finance, these models are capable to include an organization's or individual's ongoing finance status to predict, for example, the probability of or ....High Predictive Performance Models via Semi-Parametric Survival Regression. This project will develop novel statistical models for high prediction performance. When applied to help doctor to treat patients, these models allow the users to include gene or other biomarkers for predicting effectiveness of a treatment. When applied to risk management in finance, these models are capable to include an organization's or individual's ongoing finance status to predict, for example, the probability of or time to loan default. Innovative computational methods will be developed for fitting these models. Compared to traditional prediction method, this approach allows greater flexibility while being superior in terms of statistical accuracy and bias. Extensive analyses of healthcare data from diverse fields will be undertaken.Read moreRead less
New statistical approaches for analysing foodwebs and species distributions. Identifying how species are distributed over the landscape, interact and self-organise into foodwebs are central goals in Ecology. This project aims to provide innovative new Bayesian modelling tools to improve our understanding of species distributions and their foodweb networks. It is expected to develop a general framework for extending species distribution models to deal with multiple species, incorporating both the ....New statistical approaches for analysing foodwebs and species distributions. Identifying how species are distributed over the landscape, interact and self-organise into foodwebs are central goals in Ecology. This project aims to provide innovative new Bayesian modelling tools to improve our understanding of species distributions and their foodweb networks. It is expected to develop a general framework for extending species distribution models to deal with multiple species, incorporating both their interactions as well as errors in detection. The project also hopes to develop a robust Bayesian methodology for partitioning complex foodweb networks into ecologically relevant compartments as there are currently no reliable methods to achieve this. Both projects are of relevance to conservation policy and management of threatened species.Read moreRead less
Improved models to understand the genomic architecture of complex traits. This project aims to improve modelling of the genetics underlying complex traits. The project will develop and test models for using genome-wide genetic data to investigate how much heritability (genetic effect) underlies traits of interest, where it lies in the genome, and how much of it is shared across traits. The new models will be implemented in statistical algorithms in a freely-available software package. This proj ....Improved models to understand the genomic architecture of complex traits. This project aims to improve modelling of the genetics underlying complex traits. The project will develop and test models for using genome-wide genetic data to investigate how much heritability (genetic effect) underlies traits of interest, where it lies in the genome, and how much of it is shared across traits. The new models will be implemented in statistical algorithms in a freely-available software package. This project expects to increase understanding of biological mechanisms, the efficiency of genetic association analyses and the accuracy of genomic prediction, including the effects of interventions. The project will adapt human models to a wider range of organisms, in particular bacteria.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100046
Funder
Australian Research Council
Funding Amount
$387,000.00
Summary
Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established ....Fortifying our digital economy: advanced automated vulnerability discovery. This project aims to enable security researchers to detect critical vulnerabilities in large software systems with maximal efficiency, cost-effectively, and with known statistical accuracy. The aim is to develop advanced high-performance fuzzers that effectively thwart malware attacks, ransomware epidemics, and cyber terrorism by exposing security flaws before they can commence. The project will employ a well-established statistical framework utilised in ecology research to provide fundamental insights to boosting the efficiency of software vulnerability discovery, and on the trade-off between investing more resources and gaining better cyber security guarantees. As our reliance on new technologies is ever growing, this project equips Australia to curb cyber crime cost-effectively.Read moreRead less