Sih-Jing Liao

Doctor of Philosophy, (Statistics)
Study Completed: 2020
College of Sciences

Citation

Thesis Title
Statistical modelling of zoonotic diseases

Using statistical modelling to trace sources of zoonoses provides valuable information about disease transmission. This helps policy makers to design and implement appropriate strategies for disease prevention and intervention. However, advances in source attribution modelling have slowed down in recent years. Ms Liao paved the way for a new generation of models based on the full integration of epidemiology and genomics using flexible statistical frameworks. She applied the developed models to New Zealand campylobacteriosis data and found that urban cases are more likely to be associated with poultry, while rural cases are of ruminant origin. With appropriate tailoring, these models can in principle be applied to a host of other zoonoses and the modelling frameworks are also sufficiently broad to admit any relevant covariates. Ms Liao’s research has been successful in demonstrating ‘proof of concept’ for this approach.

Supervisors
Professor Martin Hazelton
Associate Professor Jonathan Marshall
Distinguished Professor Nigel French