3 September 2021

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.

We used data from Aotearoa New Zealand’s Integrated Data Infrastructure (IDI) to create a co-incidence network of workplace employment and school enrolment. In this study we summarise the methods used to create the ACN, and detail the ways in which it can be used to inform the Aotearoa New Zealand response to disease outbreaks, such as COVID-19.

Specifically, we show how analysis of the network can be used to inform the strategy of mitigating existing outbreaks (“stamp-it-out”) by revealing those sets of areas between which an outbreak is likely to spread most quickly. We also show how analysis of the network structure can reveal spatially limited communities which can inform regional responses to disease outbreak (i.e., regional based interventions) should they need to occur, as well as specific areas of high transmission risk – both of these results can be used to aid a “prepare-for-it” strategy.

Finally, we cross-reference our findings with data on disease vulnerabilities (i.e., long-term health conditions, ethnicity, and deprivation) to highlight specific areas with a combination of high risk of contagious disease transmission and elevated vulnerability to such diseases. A web-based app, developed alongside this publication allows for visualisation and exploration of transmission risk and vulnerability and is presented as a useful tool for decision and policy makers to inform more equitable responses to diseases such as COVID-19.

Key points

 

  • The Aotearoa Co-incidence Network (ACN) represents the connections induced by interactions between individuals from dwellings in different regions of Aotearoa. The ACN details the number of connections made through shared workplaces and schools, which gives an indication of likely transmission spread should an outbreak of disease (e.g., COVID-19) occur.
  • The ACN makes no assumptions about the likely point of occurrence for an initial outbreak. That is, the transmission risk represented is an estimate of the risk of onward transmission to a region, for an initial outbreak that occurs at an arbitrary location in the country. Clearly, some regions (e.g. those with MIQ facilities and international airports) are at higher risk of being locations for seeding an outbreak. Such additional information should be considered alongside the ACN.
  • We identify several spatially contiguous communities in the ACN based on the patterns of connections. Interestingly, these communities are similar to the Territorial Authority (TA) boundaries, with some exceptions. The communities tend the cover multiple TAs, and in some cases extend boundaries. For example, the community detected in the Auckland region covers Auckland TA but also extends further south. This community more closely reflects the actual region covered when Alert Level 3 was implemented in the Auckland region in August 2020.
  • We use PageRank centrality to highlight geospatial areas that have the highest transmission risk based on the structure of connections in the ACN. Cross-referencing transmission risk with data on vulnerability allows us take an equity- focused approach to determining areas most in need of support (be that from governmental, iwi, or community sources).
  • We find that the regions with highest risk for transmission are located in urban areas, especially Hamilton, Wellington, and Palmerston North. Areas of low-transmission risk include Thames-Coromandel, Mackenzie, and Waitomo.
  • When we consider the intersection of transmission risk and vulnerability, we find that the most at risk regions include places such as South Auckland, Invercargill, Whanga ̄rei, New Plymouth, and Napier, as well as Wellington and Hamilton.