Speaker
Description
The spread of infectious diseases is fundamentally shaped by who contacts whom, when, and for how long. Contact networks capture the population-level structure of these interactions, yet explicitly recorded networks are rarely available, forcing outbreak models to rely on simplifying assumptions. Understanding how interpersonal contact patterns vary across contexts could meaningfully improve our ability to model disease outbreaks. Experimental epidemic games ("epigames") offer a controlled approach to this problem, using a gamified, Bluetooth-enabled smartphone app to simulate outbreaks among participants in real time.
We analysed five epigame networks from diverse settings (conferences and campuses, 2020–2025, in the UK, US and China), characterising their structure using structural, spectral, temporal, and epidemic metrics. We demonstrated that epigames capture realistic, high-resolution contact networks across social contexts, validating their use as a tool for studying real-world transmission dynamics.
Building on this, we investigated how the temporal properties of these networks drive their epidemic properties. We explored how features such as contact timing, contact persistence or temporal reachability, shape outbreak dynamics; linking temporal network structure directly to epidemic outcomes. Running epigames across diverse settings, ages, and demographics will be essential for ensuring that the resulting epidemic models are both accurate and equitable.
