Using the FluTracking survey data for 2021 up until the week ending 29 August 2021, we can estimate the weekly incidence (new onset) of COVID-19-like symptoms within different age groups and different parts of the country.
We use an individual-based, Aotearoa-specific Contagion Network Model to simulate the spread of COVID-19 in the community for an outbreak comparable to that detected on 17 August 2021.
Updated modelling exploring how high rates of vaccine coverage might reduce the health burden from COVID-19 if combined with moderate public health measures to reduce transmission of the virus.
This report details the methods used for calculating the estimated weekly incidence of COVID-19-like and influenza-like illness in Aotearoa New Zealand, using data from the FluTracking weekly survey.
In the first weeks of the 2021 Auckland August COVID-19 outbreak, the contagion network team provided a number of reports to officials with estimates of the likely size of the outbreak and updates on the estimated effect of Alert Level interventions on curtailing spread.
We use a range of data sources and analytic approaches to estimate the number of movements between regions of Aotearoa and to give some estimates of the risk of transmission of COVID-19 to regions outside of Auckland, during the early stages of the August 2021 outbreak.
Two technical reports in which we consider the epidemic course for the August 2021 cluster following the shift to Alert Level 4 restrictions in New Zealand, using a stochastic branching process model.
Exploring COVID-19 transmission risk and vulnerability through the Aotearoa Co-incidence Network (ACN)
The Aotearoa Co-incidence Network (ACN) provides a highly insightful tool to explore the manner in which the regions of Aotearoa New Zealand are connected to each other through co-incidence of individuals at workplaces and schools.
Three network modelling reports that explore policy settings and possible interventions to prepare for the emergence of COVID-19, whether Alert Level 2.5 can be effectively used for future outbreaks, and a large number of combinations of transmission reduction interventions.
We use a mathematical model to estimate the effect of New Zealand’s vaccine rollout on the potential spread and health impacts of COVID-19 and the implications for controlling border-related outbreaks.
A reflexive thematic analysis of Prime Minister Jacinda Ardern’s addresses to the nation and her daily press briefings with the Director-General of Health, Ashley Bloomfield.
We use a stochastic model of COVID-19 transmission and testing to investigate the effect that vaccination of border workers has on the risk of an outbreak in an unvaccinated community.
We describe the development of a stochastic mathematical model for the transmission and control of Covid-19 in New Zealand.
Te Pūnaha Matatini researchers model the effects of various different border policies and testing regimes for frontline border workers on COVID-19 reincursion risk.
We compare the economic costs of containing Auckland’s August COVID-19 outbreak using Alert Level 3 to those that might have resulted from the use of Alert Level 4.
This report – a letter prepared on behalf of Te Pūnaha Matatini Whānau – is a call for action to support emerging researchers in Aotearoa at this critical time.
Our researchers simulate the re-emergence and spread of COVID-19 in July/early August 2020, using a network model of all ~5 million people in Aotearoa New Zealand.
This paper summarises the modelling advice provided to Cabinet during the Auckland August 2020 outbreak, as well as detailing the methods used to provide that advice.
Our researchers find that the current effective reproduction number for COVID-19 in Auckland and the likelihood of cases occurring in other regions remains uncertain.
Te Pūnaha Matatini investigators evaluate the prevalence and nature of COVID-19-related disinformation and unreliable narratives in New Zealand Aotearoa social media.
Our latest research suggests that COVID-19 contact tracing digital tools such as smartphone apps need to be designed to work hand in hand with manual contact tracing.
Te Pūnaha Matatini researchers estimate the risk of community COVID-19 outbreak originating at the New Zealand border and provide some recommendations for managing future risk.
Our modeling has shown that a high-quality, rapid contact tracing system, combined with strong support for people in quarantine or isolation, can be highly effective in reducing the spread of COVID-19.
Our researchers modelled various New Zealand border control measures and scenarios to assess the risk of COVID-19 re-entering the country from incoming international travellers.
Te Pūnaha Matatini researchers estimate there is a 95% probability that COVID-19 has been eliminated in Aotearoa New Zealand after 2-3 weeks with no new reported cases.
Our researchers use a stochastic model to simulate COVID-19 spread in New Zealand, and report an estimate for its effective reproduction number (Reff) before and after implementation of Alert Level 4.
Te Punaha Matatini researchers have developed a structured model to look at the spread of COVID-19 in different groups within the New Zealand population.
A New Zealand-specific interactive epidemic simulation app developed by Dr Audrey Lustig, Associate Investigator at Te Pūnaha Matatini, and hosted by the University of Auckland’s Centre for eResearch, has just been released.
An analysis of interventions used around the world, equivalent to New Zealand’s Alert Levels 1-4, and their effect on the ability of COVID-19 to reproduce effectively.
How equitable is our healthcare system? Our researchers and colleagues analysed available data to estimate COVID-19 infection fatality rates by ethnicity in Aotearoa New Zealand.
Our investigators model COVID-19 containment and elimination scenarios in New Zealand, as the country considers an exit from a four-week period of strong population-wide control measures.
Our researchers compared suppression and mitigation strategy outcomes in COVID-19 using a simple model with New Zealand-specific parameters.