A data-driven framework for managing and monitoring novel and endemic infectious diseases in Australia: Four essays

Abstract

Over the past decade there has been a substantial increase in the number of severe infectious disease outbreaks worldwide. Amalgamated with climate change, increased air travel and population growth, there is a strong need for foundational pandemic preparedness plans featuring data and evidence-based models at their core.

This research shifts the dial of what should be considered fundamental to pandemic preparedness and planning from a data and modelling perspective. Due to recent technological advances, the role and importance of data in decision making is still relatively novel. However, this does not mean that the establishment of data-driven functions should be delayed.

This thesis develops a framework for managing and monitoring novel and endemic infectious diseases in Australia, with a focus on the role of individual behaviours in influencing disease spread outcomes. The methodology has covered the development of an agent-based microsimulation model with individual behaviours, an early warning system to monitor infectious disease cases and potential waves, and an evidence-based scenario tool for monitoring disease spread, effectively embedding a "pandemic pulse" into preparedness capability.

This framework was established via the use of Agent Based Models and econometric techniques to generate a simple-to-use series of tools that can be embedded into business-as-usual pandemic planning and preparedness activities. This research found that incorporation of behavioural parameters greatly enhances the way disease spread trajectories can be modelled, which when coupled with econometric early warning systems can be used to generate a scenario tool for modelling the likely impact of interventions prior to the signalled wave.

This research allows a better understanding of emerging and existing infectious diseases and how they might affect the Australian population. By improving our understanding of likely disease outcomes, decision makers are empowered to inform public health measures that target the minimisation of individual harm and mortality associated with an infectious disease.