Using a co-incidence network to reveal human interaction patterns

ABSTRACTS
Schools and workplaces are some of the most important connectors within societies – inducing interactions between people who often live quite far apart and would be otherwise unconnected. These co-incident interactions play an important role in sharing information and cultural practices, but also in the transmission of respiratory disease. We used linked micro-data within the Statistics NZ Integrated Data Infrastructure (IDI) to construct the Aotearoa Co-incidence Network (ACN) – a weighted, multiplex network that describes how different geospatial areas are connected to one another through people interacting at workplaces and schools. We’ll show how co-incidence networks such as this can be used to reveal the structure of interaction patterns between people while balancing concerns on privacy and anonymity that arise when working with microdata.

ABOUT THE SPEAKERS

* Dr. Dion O’Neale
– Programme Co-Lead, COVID-19 Modelling Aotearoa (https://www.covid19modelling.ac.nz)
– Principal Investigator, Te Pūnaha Matatini – a New Zealand Centre of Research Excellence
– Senior Lecturer, Physics Department, University of Auckland

* Dr. Emily Harvey
– Senior Consultant/Researcher, Market Economics Ltd, Auckland, NZ
– Co-lead of the Network Contagion Modelling team, COVID-19 Modelling Aotearoa (https://www.covid19modelling.ac.nz)
– Principal Investigator, Te Pūnaha Matatini – a New Zealand Centre of Research Excellence
– Honorary Academic, The University of Auckland