Between February and May 2020, New Zealand recorded 1504 cases of COVID-19 before eliminating community transmission of the virus in June 2020. During this period, a series of control measures were used including population-wide interventions implemented via a four-level alert system, border restrictions, and a test, trace, and isolate system. Mathematical modelling played a key role in informing the government response and guiding policy development. In this paper, we describe the development of a stochastic mathematical model for the transmission and control of COVID-19 in New Zealand.
We developed a stochastic model for COVID-19 in New Zealand that used data on cases with a recent history of international travel as seed cases. We did not attempt to predict cases arriving into New Zealand, only the subsequent chains of transmission originating from each imported case. This includes features such as superspreading, case under-ascertainment, testing and reporting delays, and population-wide and case-targeted control measures. We show how the model was calibrated to New Zealand and international data. We describe how the model was used to compare the effects of various interventions in reducing spread of the virus and to estimate the probability of elimination.
Mathematical modelling has played a key role in informing New Zealand’s response to the COVID-19 pandemic. This included the decision to ‘go hard, go early’ and issue stay-at-home orders from 25 March 2020, as well as the timing of relaxation of alert levels. Public communication of the science behind the response, in the mainstream media, social media and via interactive web apps, helped build public understanding and trust in government decision-making.
The capacity of modelling tools and the data pipelines on which they rely has been built up over a very short space of time. Ongoing investment in mathematical modelling expertise and the structures, systems, and relationships needed to provide model-based policy and operational advice will help increase Aotearoa New Zealand’s capacity to manage infectious diseases and increase preparedness for future pandemics
[Full paper] (https://doi.org/10.1080/03036758.2021.1876111)