Agent-Based Land Change Modeling of a Large Watershed: Space-Time Locations of Critical Threshold

Present day risk assessment on the spreading of airborne viruses is often based on the classical Wells-Riley model assuming immediate mixing of the aerosol into the studied environment. Here, we improve on this approach and the underlying assumptions by modeling the space-time dependency of the aerosol concentration via a transport equation with a dynamic source term introduced by the infected individual(s). In the present agent-based methodology, we study the viral aerosol inhalation exposure risk in two scenarios including a low/high risk scenario of a “supermarket”/“bar”. The model takes into account typical behavioral patterns for determining the rules of motion for the agents. We solve a diffusion model for aerosol concentration in the prescribed environments in order to account for local exposure to aerosol inhalation. We assess the infection risk using the Wells-Riley model formula using a space-time dependent aerosol concentration. The results are compared against the classical Wells-Riley model. The results indicate features that explain individual cases of high risk with repeated sampling of a heterogeneous environment occupied by non-equilibrium concentration clouds. An example is the relative frequency of cases that might be called superspreading events depending on the model parameters. A simple interpretation is that averages of infection risk are often misleading. They also point out and explain the qualitative and quantitative difference between the two cases—shopping is typically safer for a single individual person.

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Mase

Advances in Computational Intelligence and Robotics - Multi-Agent-Based Simulations Applied to Biological and Environmental Systems ◽

10.4018/978-1-5225-1756-6.ch005 ◽

2017 ◽

pp. 106-127 ◽

Cited By ~ 2

Author(s):

Celia G. Ralha ◽

Carolina G. Abreu

Keyword(s):

Land Use ◽

Conceptual Model ◽

Model Complexity ◽

Land Change ◽

Map Comparison ◽

Agent Based ◽

Change Models ◽

Multi Agent ◽

Definition Of ◽

Simulation Parameters

This chapter presents research carried out under the MASE project, including the definition of a conceptual model to characterize the behavior of individuals that interact in the dynamics of land-use and cover change. A computational tool for analyzing environmental scenarios of land change was developed, called MASE - Multi-Agent System for Environmental Simulation. MASE enables agent-based simulation scenarios and integrates the influence of socio-economic and political dynamics through the interaction of agents with rules of land-use and planning policies and the environmental physical and spatial variables. MASE simulator was extended to implement the Belief-Desire-Intention (BDI) model, called MASE-BDI. MASE and MASE-BDI are discussed including the conceptual model complexity and statistical techniques of map comparison to land change models. Two real cases of the Brazilian Cerrado validate quantitative and qualitative aspects of MASE and MASE-BDI simulators. Finally, the authors present some auto-tuning aspects of adjusting simulation parameters of MASE-BDI.

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