Paper
3 November 2008 Agent-based modeling to simulate the dengue spread
Chengbin Deng, Haiyan Tao, Zhiwei Ye
Author Affiliations +
Proceedings Volume 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments; 71431O (2008) https://doi.org/10.1117/12.812589
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
In this paper, we introduce a novel method ABM in simulating the unique process for the dengue spread. Dengue is an acute infectious disease with a long history of over 200 years. Unlike the diseases that can be transmitted directly from person to person, dengue spreads through a must vector of mosquitoes. There is still no any special effective medicine and vaccine for dengue up till now. The best way to prevent dengue spread is to take precautions beforehand. Thus, it is crucial to detect and study the dynamic process of dengue spread that closely relates to human-environment interactions where Agent-Based Modeling (ABM) effectively works. The model attempts to simulate the dengue spread in a more realistic way in the bottom-up way, and to overcome the limitation of ABM, namely overlooking the influence of geographic and environmental factors. Considering the influence of environment, Aedes aegypti ecology and other epidemiological characteristics of dengue spread, ABM can be regarded as a useful way to simulate the whole process so as to disclose the essence of the evolution of dengue spread.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chengbin Deng, Haiyan Tao, and Zhiwei Ye "Agent-based modeling to simulate the dengue spread", Proc. SPIE 7143, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 71431O (3 November 2008); https://doi.org/10.1117/12.812589
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Cited by 9 scholarly publications.
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KEYWORDS
Diffusion

Data modeling

Animal model studies

Ecology

Lithium

Monte Carlo methods

Computer simulations

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