Supervisors:
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Working Thesis:
Modelling the interaction between ethnicity and infectious disease transmission dynamics
This work aims to fill a gap in epidemiology literature identified during the COVID-19 pandemic in Aotearoa by developing models that explicitly consider ethnicity as a factor. These models could then be used as a base in pandemic scenarios to quickly and effectively inform policy makers on how their decisions would affect minority groups, which existing models were unable to do during the last pandemic.
During the COVID-19 pandemic, Aotearoa followed an elimination strategy followed by a mitigation strategy, which saw high success and kept health impact low. However, there were inequities in health outcomes, notably that M膩ori and Pacific Peoples had lower vaccine coverage and experienced higher age-standardised rates of hospitalisation and death. Models provide predictions of disease spread and burden, which can effectively inform policy, but are often less good at including inequities/heterogeneity. Despite the differences in health outcomes, most models have not explicitly considered ethnic heterogeneities as factors. We are developing some models/techniques to do so:
- An ethnicity-stratified SEIR model to analysed Omicron in Aotearoa
- Methods to combined ethnicity and age contact matrices
- An ethnicity-age-stratified model to analyse measles in Aotearoa
- An ethnicity-stratified agent based/braching process model
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Research interests:
Mathematical modelling, interdisciplinary work, ethnic equity.
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Academic history:
Bachelor of Science in Matematics and Physics, 成人大片, New Zealand.
