The Covid-19 pandemic demonstrated the value of mathematical models for informing policy decisions and the public health response to infectious disease threats. However, a major flaw in many models is that they either overlook or poorly characterise differences in disease burden between population subgroups. In New Zealand, Māori and Pacific populations have disproportionately worse health outcomes from infectious diseases and pandemics, but current cutting-edge models cannot account for the disparity in infectious disease vulnerability in these populations.
Our project will create new modelling methods that account for the diversity of vulnerability within and between populations. We have two research aims:
Aim 1. Develop new mathematical models that can capture differential dynamics of disease transmission within and between population subgroups, such as ethnicity groups or deprivation index. This will enhance understanding of epidemic dynamics by using stratified models to simulate the behaviour of future epidemic events.
Aim 2. Apply and validate these models using recent case studies on differences between ethnicity groups in Aotearoa New Zealand. We will parameterise and validate our models using anonymised age- and ethnicity-specific data, as well as linked health, Census and administrative data from Stats NZ, the Ministry of Health and Te Whatu Ora.
