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
Mathematical models of diseases with complex transmission routes. This project aims to model diseases that spread via a mixture of routes including food, water, the environment, and direct spread between individuals. Key diseases include: avian influenza, which causes massive disruption to the poultry industry; gastroenteritis, which costs Australia $1,250 million each year; and leptospirosis, which causes one million severe illnesses each year globally. This project will develop mathematical a ....Mathematical models of diseases with complex transmission routes. This project aims to model diseases that spread via a mixture of routes including food, water, the environment, and direct spread between individuals. Key diseases include: avian influenza, which causes massive disruption to the poultry industry; gastroenteritis, which costs Australia $1,250 million each year; and leptospirosis, which causes one million severe illnesses each year globally. This project will develop mathematical and statistical tools to better estimate risk, analyse outbreak data, and provide guidance for disease control. This research will improve policy and enhance our ability to respond to disease outbreaks.Read moreRead less
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
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
Binary regression with additive predictors: new statistical theory with healthcare applications. This project will develop new statistical analysis techniques for predicting whether someone is at risk of adverse health outcomes. The project will then apply the new techniques to a large database on heart attacks, leading to new insights into how patient characteristics and treatments affect the chance of dying from a heart attack.
Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provi ....Fitting non-Gaussian diffusion models to evolutionary data: towards a generalized framework for phylogenetic comparative analyses. This project aims to develop cutting-edge statistical methods for evolutionary biology in order to answer big questions using data derived from multiple species. Such methods are needed because of the variety of multi-species data that are becoming available, which cannot be dealt with correctly using current methods. The research is significant because it will provide a new way of fitting a wide class of statistical models to evolutionary data, in a very general setting. Further, this project will unite current methodology in a broader framework so that the proposed new methods are a generalisation of currently accepted theory. The outcomes will include a freely-available software package that implements the methods in a user-friendly form.Read moreRead less
Statistical methods for the analysis of critical care data, with application to the Australian and New Zealand Intensive Care Database. The recent inquiry into Queensland's Bundaberg Base Hospital highlights the need to monitor hospital performance. This project develops new statistical methods to account for uncertainty in the assessment of provider performance and its outcomes will provide government with institutional comparisons for policy and planning.
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