Cited by 126Mathematical and Theoretical Epidemiology and Ecology ModelsCOVID-19 epidemiological studiesdemographic modeling and climate adaptation

An open-data-driven agent-based model to simulate infectious disease outbreaks

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Hunter, Elizabeth, Mac Namee, Brian, Kelleher, John·2018·PLOS ONE

Abstract

Agent-based models are a tool that can be used to better understand the dynamics of an infectious disease outbreak. An infectious disease outbreak is influenced by many factors including vaccination or immunity levels, population density, and the age structure of the population. We hypothesize that these factors along with interactions of factors and the actions of individuals would lead to outbreaks of different size and severity even in two towns that appear similar on paper. Thus, it is necessary to implement a model that is able to capture these interactions and the actions of individuals. Using openly available data we create a data-driven agent-based model to simulate the spread of an airborne infectious disease in an Irish town. Agent-based models have been known to produce results that include the emergence of patterns and behaviours that are not directly programmed into the model. Our model is tested by simulating an outbreak of measles that occurred in Schull, Ireland in 2012. We simulate the same outbreak in 33 different towns and look at the correlations between the model results and the town characteristics (population, area, vaccination rates, age structure) to determine if the results of the model are affected by interactions of those town characteristics and the decisions on the agents in the model. As expected our results show that the outbreaks are not strongly correlated with any of the main characteristics of the towns and thus the model is most likely capturing such interactions and the agent-based model is successful in capturing the differences in the outbreaks.

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  1. [2]Mac Namee B, Cunningham P. Creating Socially Interactive Non Player Characters: The -SIC System. International Journal of Intelligent Games and Simulation. 2003; 2(1): 186– 221.

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Authors
Hunter, E., Mac Namee, B., & Kelleher, J.
Affiliations
Technological University Dublin (IE)
Corresponding author
Hunter, Elizabeth
Venue
PLOS ONE
Published
2018-12-19
Volume
13
Issue
12
Pages
e0208775
ISSN
1932-6203 (ISSN-L)
OpenAlex
W2905576123
Cited by
126
References
31
Citations by year
2026: 8 · 2025: 16 · 2024: 15 · 2023: 7 · 2022: 22 · 2021: 28 · 2020: 27 · 2019: 3
FWCI
13.80
Type
journal article
Language
en
Open access
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Arrow - TU Dublin (Technological University Dublin) (submittedVersion, cc-by-nc-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (submittedVersion, cc-by)
  • Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion, cc-by-nc-nd)
Funders
Fiosraigh Scholarship Program
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › demographic modeling and climate adaptation
Keywords
agent-based modeling, infectious disease outbreaks, measles, airborne transmission, open data, vaccination coverage, age structure, population density, emergent behavior
MeSH terms
Adolescent, Adult, Child, Child, Preschool, Cities, Communicable Diseases, Computer Simulation, Disease Outbreaks, Humans, Infant, Infant, Newborn, Ireland, Models, Biological, Schools, Systems Analysis, Young Adult, Geography, Medical

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