Human skin equivalent constructs: enhanced culturing and application of laboratory-grown skin through mathematical modelling and in silico experimentation. Laboratory-grown human skin equivalent constructs, given social and legislative imperatives, will be critical for advances in novel treatment protocol definitions for wound repair, dermatogical screening of pharmacueticals and fundamental studies of skin diseases.
In silico studies undertaken in this project will make a significant contrib ....Human skin equivalent constructs: enhanced culturing and application of laboratory-grown skin through mathematical modelling and in silico experimentation. Laboratory-grown human skin equivalent constructs, given social and legislative imperatives, will be critical for advances in novel treatment protocol definitions for wound repair, dermatogical screening of pharmacueticals and fundamental studies of skin diseases.
In silico studies undertaken in this project will make a significant contribution to the effectiveness of the application of human skin constructs, by delivering new and deeper insights into the interplay between dependent processes that regulate the behaviour of skin, in vivo or ex vivo. The models and the researchers associated with this project will drive innovative studies in medical science over the next decade.Read moreRead less
New data-driven mathematical models of collective cell motion. Cancer and chronic wounds are a national, and indeed, international health problem set to worsen as our population ages. Predictive and interpretive tools are required to improve our understanding of collective cell migration in relation to cancer and chronic wounds. This project will produce new validated mathematical tools for predicting collective cell migration in a general framework that can deal with application-specific detail ....New data-driven mathematical models of collective cell motion. Cancer and chronic wounds are a national, and indeed, international health problem set to worsen as our population ages. Predictive and interpretive tools are required to improve our understanding of collective cell migration in relation to cancer and chronic wounds. This project will produce new validated mathematical tools for predicting collective cell migration in a general framework that can deal with application-specific details, such as the role of cell shape and cell size. Although cell shape and size are known to affect collective cell migration, standard mathematical models ignore these details. This project will produce new predictive mathematical modelling tools that are validated by new experimental data. Read moreRead less
Modelling cell invasion incorporating the epithelial to mesenchymal transition: Exploring therapies to control wound healing and cancer progression. Cancer and wounds are closely related, commonly lethal, diseases. Both require cell growth and invasion. This project will apply experimental measurements to create new mathematical models of cancer and wounds; models that will inform new targets and strategies for the treatment of these deadly diseases.
Understanding mutation and genetic reassortment in viruses: new mathematical models of viral dynamics and evolution. This project aims to understand how evolutionary processes and ecological conditions combine to ignite and sustain viral epidemics. Using novel mathematical models and statistical methods we will study the manner in which viral genes mutate and are recombined, as well as the rates of these important forces.
Microbial natural history and molecular evolution. This project aims to develop mathematical and computational models of microbial evolution that capture dynamics at both within-host and between-host scales, combined with processes of mutation. Integration of these elements with computational statistical methods will produce a framework that will enable inference from genome sequencing data. The mathematical models will be applied to bacterial genomic data to investigate how natural selection ac ....Microbial natural history and molecular evolution. This project aims to develop mathematical and computational models of microbial evolution that capture dynamics at both within-host and between-host scales, combined with processes of mutation. Integration of these elements with computational statistical methods will produce a framework that will enable inference from genome sequencing data. The mathematical models will be applied to bacterial genomic data to investigate how natural selection acts on experimental and natural populations of microorganisms. The mathematical models and statistical approaches developed here are intended to be applicable to infectious disease of both humans and domesticated animals, and could influence public health policies.Read moreRead less
New methods for integrating population structure and stochasticity into models of disease dynamics. Epidemics, such as the 2007 equine 'flu outbreak and 2009 swine 'flu pandemic, highlight the need to make informed decisive responses. This project will develop new methods that incorporate two important aspects of disease dynamics---host structure and chance---into mathematical models, and determine their impact in terms of controlling infections.
Developing mathematical models of infection and transmission to link biology, epidemiology and public health policy. Infectious diseases constitute a significant burden on the health of the population. Understanding how best to control them requires a multi-faceted approach, combining data from biology, medicine and population health with mathematical and computational models of disease transmission. This project will investigate the "flu" and other diseases.
Optimising progress towards elimination of malaria. The project aims to advance mathematical knowledge by developing novel tools appropriate for modelling disease elimination. We will apply these new mathematical tools to the significant problem of malaria elimination in Vietnam. The expected outcomes are new tools for modelling disease elimination on a fine spatial resolution with heterogeneities in individual patient characteristics, calibrating models to household level data on disease transm ....Optimising progress towards elimination of malaria. The project aims to advance mathematical knowledge by developing novel tools appropriate for modelling disease elimination. We will apply these new mathematical tools to the significant problem of malaria elimination in Vietnam. The expected outcomes are new tools for modelling disease elimination on a fine spatial resolution with heterogeneities in individual patient characteristics, calibrating models to household level data on disease transmission and designing intervention strategies for maximum effect on disease transmission. The innovative combination of modelling, inference and optimisation ensures that the mathematical methods developed will be broadly applicable to modelling elimination strategies for other infectious diseases.
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Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and r ....Epidemics in large populations: long-term and near-critical behaviour. The project aims to prove qualitative and quantitative results concerning aspects of the long-term behaviour of near-critical epidemics, including the probability and duration of a large outbreak, and the total number of people infected. This project is a theoretical study of stochastic models of epidemics in large populations. The project will focus on emerging epidemics, where the average number of contacts, infection and recovery rates are such that the basic reproduction number of the disease is near the critical value 1. The project will plan to both analyse particular epidemic models and develop new methodologies applicable in broader contexts. The mathematical predictions will be tested through simulations and comparison to real-world data. The significant outcome of the project should be the advancement in mathematical understanding of infectious disease spread, eventually leading to improved epidemic surveillance and control, and resulting in more effective protection of public health, improved quality of life, and obvious economic benefits.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE120101529
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Transmission dynamics modelling of zoonotic neglected tropical diseases. This project will develop mathematical models to simulate zoonotic disease transmission and control. Results will provide novel insight for policy makers into effective interventions for schistosomiasis, echinococcosis and clonorchiasis, as well as provide a methodological platform for adaptation to other zoonotic emerging and re-emerging diseases.