Software 'agents' modelled on real-life individuals will be used by University of Sydney researchers to develop high-precision computer models that can predict where or when an epidemic may strike.
Our software "agents" will be constructed using information from the Australian Census
Professor Mikhail Prokopenko, Complex Systems Research Group director, School of Civil Engineering will lead the research project funded recently by the Australian Research Council.
The professor says:
“We want to improve the accuracy of modern epidemiological models. We are aiming to integrate large-scale datasets and the explicit computer simulation of entire populations down to the scale of a single individual”.
“We will couple our software “agents” with “what if” scenarios to improve the forecasting of the various twists and turns of a developing epidemic.
“Our software "agents" will be constructed using information from the Australian Census with attributes typical of any individual, such as age, gender, household status, occupation, and sector of employment, as well as a set of health characteristics including the susceptibility and immunity to diseases.
By simulating interactions of these "agents", with respect to work, study and other activities, it is possible to trace how a specific epidemic, originated at a particular point, may develop over time.
“A recent study estimated the cost of influenza in Australia at between $828 million and $884 million per year,” states Professor Pip Pattison, Deputy Vice Chancellor (Education) and co-researcher on the project.
The specialist in the development and application of mathematical and statistical models for social networks and network processes Professor Pattison says:
“By running multiple computer simulations while varying the sources of infection, it is possible to estimate the average social and health impact, as well as "zoom in" on specific pathways and patterns of epidemics - this is very important for a detailed understanding of how diseases may spread in varying circumstances and localities, and for identifying the best ways to locate and curtail the epidemics.
“This project will provide valuable inputs to estimation and advance planning of required resources, such as hospital beds, vaccinations, transport, and so on.
We specifically aim to develop a computationally efficient large-scale simulation model of disease diffusion on a national-level for Australia,” states Professor Pattison.
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