  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.
