Abstract
In understanding the dynamics of the spread of an infectious disease, it is important to understand how a town’s place in a network of towns within a region will impact how the disease spreads to that town and from that town. In this article, we take a model for the spread of an infectious disease in a single town and scale it up to simulate a region containing multiple towns. The model is validated by looking at how adding additional towns and commuters influences the outbreak in a single town. We then look at how the centrality of a town within a network influences the outbreak. Our main finding is that the commuters coming into a town have a greater effect on whether an outbreak will spread to a town than the commuters going out. The findings on centrality of a town and how it influences an outbreak could potentially be used to help influence future policy and intervention strategies such as school closure policies.
Subject
Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health
Reference22 articles.
1. Measeles: Vaccine-Preventable Diseases Surveillance Standards,2018
2. An open-data-driven agent-based model to simulate infectious disease outbreaks
3. Creating Socially Interactive Non Player Characters: The -SIC System;Mac Namee;Int. J. Intell. Games Simul.,2003
Cited by
14 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献