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.
Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project ....Computational methods for population-size-dependent branching processes. Branching processes are the primary mathematical tool used to model populations that evolve randomly in time. Most key results in the theory are derived under the simplifying assumption that individuals reproduce and die independently of each other. However, this assumption fails in most real-life situations, in particular when the environment has limited resources or when the habitat has a restricted capacity. This project aims to develop novel and effective algorithmic techniques and statistical methods for a class of branching processes with dependences. We will use these results to study significant problems in the conservation of endangered island bird populations in Oceania, and to help inform their conservation management.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160100690
Funder
Australian Research Council
Funding Amount
$373,316.00
Summary
Mathematical modelling of the early stages of multicellular evolution. This project aims to develop new mathematical methodology to understand the early stages of the evolution of multicellular organisms from unicellular ancestors. This is the best known example of the creation of a new level of biological organisation. However, the early stages of this transition are poorly understood, especially how early groups of cells came to possess Darwinian characteristics, which then allows natural sele ....Mathematical modelling of the early stages of multicellular evolution. This project aims to develop new mathematical methodology to understand the early stages of the evolution of multicellular organisms from unicellular ancestors. This is the best known example of the creation of a new level of biological organisation. However, the early stages of this transition are poorly understood, especially how early groups of cells came to possess Darwinian characteristics, which then allows natural selection to act on them. It is anticipated that the models produced will be used to give the first mechanistic account of this intrinsically stochastic, multi-level, phenomenon. This may lead to new insights into the emergence and subsequent evolution of simple multicellular life cycles and early forms of development.Read moreRead less