Thesis Proposal Review: Surveillance and Modelling of Diseases at Low Prevalence

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About

Mathematical models are highly-powerful tools in infectious disease epidemiology. Models can shed light on the processes driving transmission and offer insight into both past and future transmission dynamics.  However, modelling emerging diseases and diseases at low prevalence has unique challenges: potentially insufficient surveillance, unknown disease and population characteristics and large uncertainties. These challenges can be overcome, but special attention must be given to model structure and parameters.

For my PhD I have been modelling two diseases: Lymphatic Filariasis (LF) at low prevalence in American Samoa and African Swine Fever (ASF) if it were to be introduced in Australia. For LF I have compared the effectiveness of a targeted surveillance and treatment strategy to traditional mass drug administration, which has so far failed to eliminate LF after multiple rounds. For ASF, I have begun to investigate the effects of feral and domestic pig population dynamics on outbreak severity and the effects of model assumptions and complexity on model output accuracy.

Bio

CallumCallum Shaw is a PhD candidate in the Centre for Public Health Data and Policy of the National Centre for Epidemiology and Population Health. Callum is supervised by Professor Kathryn Glass, Dr Angus McLure and Dr Belinda Barnes. Prior to undertaking his PhD, Callum completed his honours year and worked as a research assistant across the street at the Research School of Earth Sciences, modelling wave generation in the open ocean.