Improving the computational efficiency of an agent-based spatiotemporal model of livestock disease spread and control

Authored by R A Bradhurst, S E Roche, I J East, P Kwan, M G Garner

Date Published: 2016

DOI: 10.1016/j.envsoft.2015.11.015

Sponsors: Australian Department of Agriculture and Water Resources Australian Government

Platforms: Java SQL

Model Documentation: Other Narrative Pseudocode

Model Code URLs: Model code not found

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. (C) 2015 Elsevier Ltd. All rights reserved.

Tags

Simulation Performance Dynamics Australia Epidemic Strategies Framework Mouth-disease Mathematical-models Foot