A Model for the Spread of Infectious Diseases in a Region
Elizabeth Hunter1, Brian Mac Namee2, John D Kelleher3
1School of Computer Science, Technological University Dublin, Dublin D24 FKT9, Ireland.
Summary
Understanding infectious disease spread in networked towns is key. Incoming commuters significantly impact a town's outbreak risk more than outgoing commuters, informing public health policy.
Area of Science:
- Epidemiology
- Network Science
- Mathematical Modeling
Background:
- Understanding infectious disease dynamics requires analyzing transmission across interconnected populations.
- A town's position within a regional network influences disease spread to and from that location.
Purpose of the Study:
- To scale a single-town infectious disease model to a multi-town regional network.
- To investigate the impact of network structure and commuter flow on disease outbreaks.
- To determine how a town's centrality affects outbreak dynamics.
Main Methods:
- Developed a multi-town simulation model based on a single-town infectious disease model.
- Validated the model by assessing the influence of additional towns and commuters on a single town's outbreak.
- Analyzed the relationship between a town's network centrality and outbreak patterns.
Main Results:
- Incoming commuter flow has a greater impact on a town's susceptibility to an outbreak than outgoing commuter flow.
- A town's position and connectivity within the regional network significantly influence disease transmission dynamics.
- Network centrality emerged as a critical factor in predicting outbreak severity and spread.
Conclusions:
- Network structure and commuter patterns are crucial determinants of infectious disease spread in a region.
- Intervention strategies, such as targeted public health policies, can be informed by a town's network centrality.
- Focusing on inbound connectivity may be more effective for preventing disease introduction into a community.
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