Modeling malaria as a complex adaptive system
Artificial Life
A framework for modeling mosquito vectors
Proceedings of the 2010 Summer Computer Simulation Conference
An agent-based model of the Anopheles gambiae mosquito life cycle
Proceedings of the 2010 Summer Computer Simulation Conference
Verification & validation by docking: a case study of agent-based models of Anopheles gambiae
Proceedings of the 2010 Summer Computer Simulation Conference
Divide and conquer: a four-fold docking experience of agent-based models
Proceedings of the Winter Simulation Conference
A Spatial Agent-Based Model of Malaria: Model Verification and Effects of Spatial Heterogeneity
International Journal of Agent Technologies and Systems
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In agent-based modeling (ABM), an explicit spatial representation may be required in some cases for certain aspects of the system to be modeled more realistically. In this paper, we describe modeling space in a previous agent-based model of malaria. In the new spatial model, all agents (mosquitoes and aquatic habitats) possess explicit spatial information. The habitat locations of mosquitoes are specified according to different spatial patterns, or landscapes. We use three types of landscapes: regular, random, and hybrid. In the spatial context, we describe the modeling aspects of mosquito agents' movement, the event of oviposition (the process of laying eggs), and compare results between the two models (non-spatial and spatial). Ensuring oviposition is modeled accurately, we show that both models are docked. For both models, we investigate the effect of relative sizes of the aquatic habitats. Using different landscapes, we show that vector abundance (VA) remain unchanged. We also show that with same combined carrying capacity, varying the density of habitats in a landscape does not affect the mean population significantly. Finally, we show that when the density of aquatic habitats is constant, the combined carrying capacity drives VA.