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Understanding and preventing gun violence: A qualitative study. Gun violence causes significant harm across Australian communities. Excluding sexual assault, firearms feature in nearly one in 10 violent crimes. The annual costs of gun violence run into tens of millions of dollars. This project aims to make an original qualitative contribution to understanding and preventing gun violence in three contexts: drug dealing/trafficking, other organised crime activity, and armed robbery. The proposed r ....Understanding and preventing gun violence: A qualitative study. Gun violence causes significant harm across Australian communities. Excluding sexual assault, firearms feature in nearly one in 10 violent crimes. The annual costs of gun violence run into tens of millions of dollars. This project aims to make an original qualitative contribution to understanding and preventing gun violence in three contexts: drug dealing/trafficking, other organised crime activity, and armed robbery. The proposed research would be the first study nationally - and one of the very few internationally - to interview convicted gun crime users about the acquisition and use of firearms in criminal life. Project results are expected to have direct implications for reducing the impact of gun violence in Australia.Read moreRead less
Non-linear modelling for predicting patient presentation rates for mass-gatherings. Mass-gatherings are events where crowds gather. Access to health care at these events is critical, though difficult. Complex interrelationships exist between characteristics of events and presenting patient profiles. To prevent overwhelming local hospital and emergency services it is important to accurately predict patient volume. A predictive model constructed through linear modelling has been widely used. Key f ....Non-linear modelling for predicting patient presentation rates for mass-gatherings. Mass-gatherings are events where crowds gather. Access to health care at these events is critical, though difficult. Complex interrelationships exist between characteristics of events and presenting patient profiles. To prevent overwhelming local hospital and emergency services it is important to accurately predict patient volume. A predictive model constructed through linear modelling has been widely used. Key features affecting patient presentations are non-linear in character and non-linear modelling may provide more accurate patient predictive models. This project provides prospective analysis of data to develop a non-linear predictive model.Read moreRead less