ArticleComputers in biology and medicine2022
An agent-based model of the dual causality between individual and collective behaviors in an epidemic.
Article in Computers in biology and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 23 citations in OpenAlex.
- Simulating nationwide coupled disease and fear spread in an agent-based model.Scientific reports · 2025Article
- Adaptive behaviour during epidemics: a social risk appraisal approach to modelling dynamics.Journal of the Royal Society, Interface · 2025Article
- An epidemiological extension of the El Farol Bar problem.Frontiers in big data · 2025Article
- Susceptible-Infected-Susceptible type COVID-19 spread with collective effects.Scientific reports · 2023Article
- A stochastic agent-based model to evaluate COVID-19 transmission influenced by human mobility.Nonlinear dynamics · 2023Article
- A Bayesian predictive analytics model for improving long range epidemic forecasting during an infection wave.Healthcare analytics (New York, N.Y.) · 2022Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Research Into Mental Health Prediction of Community Workers Involved in the Prevention of COVID-19 Epidemic Based on Cloud Model.Frontiers in public health · 2022Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The evolution of an epidemic is strongly related to the behavior of individuals, and the consideration of cause and effect of social phenomena can extend epidemiological models and allow for better identification, prediction and control of the impacts of containment and mitigation measures. This work proposes an agent-based model to simulate the double causality that exists between individual behaviors, influenced by the cultural orientation of a population, and the evolution of an epidemic, focusing on recent studies on the COVID-19 pandemic. To do this, concepts from the social sciences are used, such as the theory of planned behavior, as well as Bayesian inference to abstract the decision-making processes involved in human behavior. A set of simulation experiments with different populations was developed to demonstrate the role that the cultural orientation of a population plays in the management of an epidemic. The results agree with the revised theory, showing that in populations that have a greater inclination towards collectivism, epidemiological indicators evolve in a better way than in those populations where the culture is individualistic. This work contributes to the field of computational epidemiology by providing a new way of including the social aspects of studied populations in agent-based models to help develop better interventions.
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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.