Investigating spatiotemporal dynamics and synchrony of influenza epidemics in Australia: An agent-based modelling approach
Authored by Mikhail Prokopenko, Oliver M Cliff, Nathan Harding, Mahendra Piraveenan, E Yagmur Erten, Manoj Gambhir
Date Published: 2018
DOI: 10.1016/j.simpat.2018.07.005
Sponsors:
Australian Research Council (ARC)
Platforms:
No platforms listed
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
In this paper we present ACEMod, an agent-based modelling framework for
studying influenza epidemics in Australia. The simulator is designed to
analyse the spatiotemporal spread of contagion and influenza spatial
synchrony across the nation. The individual-based epidemiological model
accounts for mobility (worker and student commuting) patterns and human
interactions derived from the 2006 Australian census and other national
data sources. The high-precision simulation comprises 19.8 million
stochastically generated software agents and traces the dynamics of
influenza viral infection and transmission at several scales. Using this
approach, we are able to synthesise epidemics in Australia with varying
outbreak locations and severity. For each scenario, we investigate the
spatiotemporal profiles of these epidemics, both qualitatively and
quantitatively, via incidence curves, prevalence choropleths, and
epidemic synchrony. This analysis exemplifies the nature of influenza
pandemics within Australia and facilitates future planning of effective
intervention, mitigation and crisis management strategies.
Tags
Agent-based modelling
Complex networks
Social networks
epidemics
Infection
demographics
Computational epidemiology
information
Influenza
disease
Outbreaks
Pandemic influenza
Strategies
United-states
Synchrony
Boolean networks
Discrete-time
simulation