Phase Transitions in Spatial Connectivity during Influenza Pandemics
Nathan Harding1, Richard Spinney1, Mikhail Prokopenko1,2
1Centre for Complex Systems, Faculty of Engineering, The University of Sydney, Sydney, NSW 2006, Australia.
This study reveals critical shifts in spatial connectivity during influenza pandemics. Analyzing epidemic spread in Australia, it identifies distinct infection patterns between urban and rural areas during different epidemic waves.
Area of Science:
- Epidemiology
- Computational modeling
- Network science
Background:
- Influenza pandemics exhibit complex spatial dynamics.
- Understanding spatial connectivity is crucial for predicting epidemic spread and implementing control measures.
Purpose of the Study:
- To investigate phase transitions in spatial connectivity during influenza pandemics.
- To relate epidemic thresholds to cluster formation based on average infection.
- To analyze spatial patterns of infection during epidemic peaks.
Main Methods:
- Utilized the Australian Census-based Epidemic Model (AceMod), a large-scale agent-based model.
- Simulated influenza spread using 2016 Australian census data for approximately 23.4 million agents.
- Applied percolation theory and Fisher Information to quantify spatial connectivity and identify critical regimes.
Main Results:
- Identified critical regimes corresponding to abrupt changes in spatial infection distribution.
- Observed distinct spatial patterns of infection in the post-critical phase between the first (national) and second (community) waves.
- Differentiated between urban and rural epidemic peaks, highlighting unique spatial characteristics.
Conclusions:
- Spatial connectivity undergoes significant transitions during influenza pandemics.
- Epidemic peaks are associated with critical phenomena in spatial infection patterns.
- Urban and rural areas exhibit different spatial infection dynamics during epidemic waves.
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