ArticleComputers in biology and medicine2021
Multi-agent simulation model for the evaluation of COVID-19 transmission.
Article in Computers in biology and medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- An agent-based secure privacy-preserving decentralized protocol for sharing and managing digital health passport information during crises.PeerJ. Computer science · 2023Article
- Multi-agent simulation model updating and forecasting for the evaluation of COVID-19 transmission.Scientific reports · 2022Article
- Did the Tokyo Olympic Games enhance the transmission of COVID-19? An interpretation with machine learning.Computers in biology and medicine · 2022Article
- Optimize data-driven multi-agent simulation for COVID-19 transmission.BMC bioinformatics · 2022Article
- Global key concepts of civil-military cooperation for disaster management in the COVID-19 pandemic-A qualitative phenomenological scoping review.Frontiers in public health · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This work proposes an agent-based model to analyze the spread processes of the COVID-19 epidemics in open regions and based on hypothetical social scenarios of viral transmissibility. Differently from other previous models, we consider the environment to be a multi-region space in which the epidemic spreads according to the dynamics and the concentration of agents in such regions. This paper suggests that software agents can provide a more suitable model for individuals, and their features, thus showing the influence of civil society in the context of pandemic management. This is achieved by modeling an individual as an agent with a wide range of features (health condition, purchasing power, awareness, mobility, professional activity, age, and gender). The model supports the design of populations and interactions akin to real-life scenarios. Simulation results show that the proposed model can be applied in several ways to support decision-makers to better understand the epidemic spread and the actions that can be taken against the pandemic.
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Registered trials
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.