Agent-based simulation for predicting COVID-19 behavior and impact on health care systems
DOI:
https://doi.org/10.59057/iberoleon.20075316.202238378Keywords:
agent-based modeling, SARS-CoV-2, complex system, pandemic, simulationsAbstract
Agent-based modeling is a technique for studying complex systems and representing actual problems, showing how individual behaviors determine the evolution of a system. Agent-based models are used in many disciplines, including health sciences, but little is known about how their application as a simulation model can help to obtain results that are very close to reality. For example, the COVID-19 pandemic is a current public health case with great potential to apply a simulation model that can show data related to vaccination, use of masks, isolation, reduced mobility, among many others, and how infections and deaths evolve. The purpose of this article is to show different scenarios, built through models focused on COVID-19 disease, regarding the use of masks and other infection control measures, such as quarantine and the capacity of the health system to understand their behavior.
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