Now showing 1 - 3 of 3
  • Publication
    Degree Centrality and the Probability of an Infectious Disease Outbreak in Towns within a Region Outbreak in Towns within a Region
    Agent-based models can be used to help study the spread of infectious diseases within a population. As no individual town is in isolation, commuting patterns into and out of a town or city are a vital part of understanding the course of an outbreak within a town. Thus the centrality of a town in a network of towns, such as a county or an entire country, should be an important influence on an outbreak. We propose looking at the probability that an outbreak enters a given town in a region and comparing that probability to the centrality of the town. Our results show that as expected there is a relationship between centrality and outbreaks. Specifically, we found that the degree of centrality of a town affected the likelihood of an outbreak within the network spreading to the town. We also found that for towns where an outbreak begins the degree of centrality of the town affects how the outbreak spreads in the network.
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  • Publication
    A Hybrid Agent-Based and Equation Based Model for the Spread of Infectious Diseases
    (SIMSOC Consortium, 2020-10-31) ; ;
    Both agent-based models and equation-based models can be used to model the spread of an infectious disease. Equation-based models have been shown to capture the overall dynamics of a disease outbreak while agent-based models are able to capture heterogeneous characteristics of agents that drive the spread of an outbreak. However, agent-based models are computationally intensive. To capture the advantages of both the equation-based and agent-based models, we create a hybrid model where the disease component of the hybrid model switches between agent-based and equation-based. The switch is determined using the number of agents infected. We first test the model at the town level and then the county level investigating different switch values and geographic levels of switching. We find that a hybrid model is able to save time compared to a fully agent-based model without losing a significant amount of fidelity.
    Scopus© Citations 21  9
  • Publication
    A Model for the Spread of Infectious Diseases in a Region
    In understanding the dynamics of the spread of an infectious disease, it is important tounderstand how a town’s place in a network of towns within a region will impact how the diseasespreads to that town and from that town. In this article, we take a model for the spread of aninfectious 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 theoutbreak in a single town. We then look at how the centrality of a town within a network influencesthe outbreak. Our main finding is that the commuters coming into a town have a greater effect onwhether an outbreak will spread to a town than the commuters going out. The findings on centralityof a town and how it influences an outbreak could potentially be used to help influence future policyand intervention strategies such as school closure policies.
    Scopus© Citations 11  170