ARC Future Fellowships - Grant ID: FT170100409

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/FT170100409

Funding Status
Active

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Funded Activity Summary

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.

Funded Activity Details

Start Date: 30-12-2017

End Date: 29-12-2022

Funding Scheme: ARC Future Fellowships

Funding Amount: $960,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Biological Mathematics | Probability Theory | Stochastic Analysis and Modelling | Statistics |

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Biological Sciences | Disease Distribution and Transmission (incl. Surveillance and Response) | Expanding Knowledge in the Mathematical Sciences

Other Keywords

Biological Mathematics | Disease Distribution and Transmission (incl. Surveillance and Response) | Expanding Knowledge in the Biological Sciences | Expanding Knowledge in the Mathematical Sciences | Probability Theory | Statistics | Stochastic Analysis and Modelling

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