The study presents an intermediate-level modeling approach using "super-agents" to simulate infection spread efficiently. Voronoi Diagram tessellations outperform standard Census Block Group tessellations, balancing accuracy and efficiency. The research aims to improve disease modeling in urban areas by leveraging real-world mobility data and strategic geospatial tessellations.
The content delves into the significance of agent-based simulation in various fields, emphasizing its role in understanding complex systems. It discusses the integration of ABM with geography to enhance disease modeling specificity. The study highlights the importance of tessellation techniques like Voronoi diagrams for efficient simulations and accurate representation of geographical details.
Furthermore, it explores the impact of reduced agent count on pandemic simulations, introducing a novel approach with "super-agents" to maintain simulation dynamics while improving computational efficiency. The experiments conducted across different cities reveal insights into tessellation strategies' performance in capturing visit patterns and co-visiting probabilities.
Overall, the content provides a comprehensive analysis of infectious disease modeling through agent-based approaches, emphasizing the importance of geographical specificity and efficient simulation techniques.
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by Amir Mohamma... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2309.07055.pdfDeeper Inquiries