The role of the mathematical sciences in supporting the COVID-19 response in Australia and New Zealand

TL;DR

This paper reviews how mathematical modelling and data analytics supported COVID-19 policy responses in Australia and New Zealand, highlighting tools, communication, and future challenges.

Contribution

It provides an overview of modelling approaches used in Australia and New Zealand's COVID-19 response and reflects on the modelling-policy interface and its impact.

Findings

Use of diverse models from short-term forecasts to long-term scenarios

Effective communication between modellers and policymakers

Identification of future challenges in pandemic modelling

Abstract

Mathematical modelling has been used to support the response to the COVID-19 pandemic in countries around the world including Australia and New Zealand. Both these countries have followed similar pandemic response strategies, using a combination of strict border measures and community interventions to minimise infection rates until high vaccine coverage was achieved. This required a different set of modelling tools to those used in countries that experienced much higher levels of prevalence throughout the pandemic. In this article, we provide an overview of some of the mathematical modelling and data analytics work that has helped to inform the policy response to the pandemic in Australia and New Zealand. This is a reflection on our experiences working at the modelling-policy interface and the impact this has had on the pandemic response. We outline the various types of model outputs, from short-term forecasts to longer-term scenario models, that have been used in different contexts. We discuss issues relating to communication between mathematical modellers and stakeholders such as health officials and policymakers. We conclude with some future challenges and opportunities in this area.