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Title: Improving the computational efficiency of an agent-based spatiotemporal model of livestock disease spread and control
Contributor(s): Bradhurst, Richard A (author); Roche, S E (author); East, I J (author); Kwan, Paul H  (author); Garner, M G (author)
Publication Date: 2016
DOI: 10.1016/j.envsoft.2015.11.015
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Abstract: Agent-based models (ABMs) are well suited to representing the spatiotemporal spread and control of disease in a population. The explicit modelling of individuals in a large population, however, can be computationally intensive, especially when models are stochastic and/or spatially-explicit. Large-scale ABMs often require a highly parallel platform such as a high-performance computing cluster, which tends to confine their utility to university, defence and scientific research environments. This poses a challenge for those interested in modelling the spread of disease on a large scale with access only to modest hardware platforms. The Australian Animal DISease (AADIS) model is a spatiotemporal ABM of livestock disease spread and control. The AADIS ABM is able to complete complex national-scale simulations of disease spread and control on a personal computer. Computational efficiency is achieved through a hybrid model architecture that embeds equation-based models inside herd agents, an asynchronous software architecture, and a grid-based spatial indexing scheme.
Publication Type: Journal Article
Source of Publication: Environmental Modelling & Software, v.77, p. 1-12
Publisher: Pergamon Press
Place of Publication: Oxford, United Kingdom
ISSN: 1873-6726
Field of Research (FOR): 070704 Veterinary Epidemiology
080102 Artificial Life
080110 Simulation and Modelling
Socio-Economic Outcome Codes: 970108 Expanding Knowledge in the Information and Computing Sciences
960405 Control of Pests, Diseases and Exotic Species at Regional or Larger Scales
890201 Application Software Packages (excl. Computer Games)
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
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