Modelling the interaction between ethnicity and infectious disease transmission dynamics in Aotearoa New Zealand during the first Omicron wave of the COVID-19 pandemic

TL;DR

This study models how ethnicity influences COVID-19 transmission in New Zealand during the Omicron wave, highlighting that disparities in transmission rates largely explain observed health inequities among different ethnic groups.

Contribution

It introduces an ethnicity-aware transmission model for COVID-19, explicitly incorporating ethnic heterogeneity and contact patterns, which previous models often overlooked.

Findings

Māori, Pacific, and Asian transmission rates differ significantly from European rates.

Ethnic disparities in transmission rates account for most of the observed health inequities.

Contact pattern assumptions have less impact on explaining disparities.

Abstract

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\=aori 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 developed such a model to investigate the first Omicron wave of the COVID-19 pandemic in Aotearoa, which was the first widespread community transmission of SARS-CoV-2. We analysed three models for contact patterns within and between ethnicities: proportionate, assortative, and unconstrained mixing, which were fit using ethnicity-specific data on reported cases and spatially disaggregated population counts. We found that M\=aori, Pacific, and Asian transmission rates were between 1.08-2.46, 1.50-3.89, and 0.80-0.92 times the European rates, respectively. We then found that from the parameters considered in the model, the disparity in ethnic transmission rates explained the majority of the observed ethnic disparity in attack rates, while assortativity and vaccination rates explained comparatively less.