Management of infectious disease outbreaks using agent-based models

The discovery of a hepatitis C (HCV) treatment has the potential to lead to disease elimination, with smaller countries such as Iceland likely to be the first to reach this goal. Beyond this, it will be critical to ensure that progress is not undone by minimising the potential for outbreaks. To understand outbreak risk and the potential impact of prevention strategies, it is important to study how HCV is transmitted between individuals. Transmission networks for HCV can be included in mathematical models, which can then be used to analyse and forecast the outcome of different scenarios. The aim of the project is to create an agent-based model to determine the probability of an HCV outbreak occurring for a given empirical transmission network structure, with data from the Burnet Institute enabling specific consideration of Melbourne, Victoria. The project will then simulate the reintroduction of HCV in the model and compare the effectiveness of different policies to detect and contain it, according to which results in the least number of affected individuals and the shortest time period before it is controlled. The model will include parameters such as the probability of infection and the prevalence of the disease in the population. The inclusion of a network-based element allows the interaction between high- and low-prevalent communities to be captured. The research output could then dictate decisions and policies on how to manage infectious diseases.