ArticlePloS one2018
An open-data-driven agent-based model to simulate infectious disease outbreaks.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
- Autochthonous dengue transmission in Europe: epidemiology, mechanisms, and modelling insights.Biology direct · 2026Review
- Modeling individual self-protective behavior during epidemics.PLoS computational biology · 2026Article
- A multi-method study evaluating the inference of compartmental model parameters from a generative agent-based model.Infectious Disease Modelling · 2026Article
- Real-time spatiotemporal tracking of infectious outbreaks in confined environments with a host-pathogen agent-based system.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Assessing the impact of misinformation during the spread of infectious diseases.Scientific reports · 2025Article
- The Role of Mathematical Modelling in Predicting and Controlling Infectious Disease Outbreaks in Underserved Settings: A Systematic Review and Meta-Analysis.Public health challenges · 2025Review
- Incorporating Additional Evidence as Prior Information to Resolve Non-Identifiability in Bayesian Disease Model Calibration: A Tutorial.Statistics in medicine · 2025Article
- Article
- Digital twins in healthcare: a comprehensive review and future directions.Frontiers in digital health · 2025Review
- BharatSim: An agent-based modelling framework for India.PLoS computational biology · 2024Article
- Integrating machine learning and artificial intelligence in life-course epidemiology: pathways to innovative public health solutions.BMC medicine · 2024Review
- Incorporating temporal information during feature engineering bolsters emulation of spatio-temporal emergence.Bioinformatics (Oxford, England) · 2024Article
- Generating synthetic population for simulating the spatiotemporal dynamics of epidemics.PLoS computational biology · 2024Article
- Planning for healthcare services during the COVID-19 pandemic in the Southeast of England: a system dynamics modelling approach.BMJ open · 2023Article
- Impact of school operating scenarios on COVID-19 transmission under vaccination in the U.S.: an agent-based simulation model.Scientific reports · 2023Article
- Modelling SARS-CoV-2 disease progression in Australia and New Zealand: an account of an agent-based approach to support public health decision-making.Australian and New Zealand journal of public health · 2022Article
- Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration.International journal of environmental research and public health · 2022Review
- Modeling COVID-19 Outbreaks in Long-Term Care Facilities Using an Agent-Based Modeling and Simulation Approach.International journal of environmental research and public health · 2022Article
- Scenario prediction of public health emergencies using infectious disease dynamics model and dynamic Bayes.Future generations computer systems : FGCS · 2022Article
- Iterative data-driven forecasting of the transmission and management of SARS-CoV-2/COVID-19 using social interventions at the county-level.Scientific reports · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.