Title: Automatic generation of agent-based models of migratory waterfowl for epidemiological analyses
Authors: Dhananjai M. Rao; Alexander Chernyakhovsky
Addresses: Computer Science and Software Engineering Department, Miami University, Oxford, OH 45056, USA ' Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Abstract: Seasonal migration of waterfowl, in which avian influenza viruses are enzootic, plays a strong role in the ecology of this disease. Consequently, detailed analysis of migratory patterns and its influence on disease ecology is needed to aid design and assessment of prophylaxis and containment strategies. Accordingly, this paper proposes a novel methodology for generating a global agent-based model involving detailed migratory patterns of waterfowl. The methodology transforms geographic information systems (GIS) data to generate metapopulation for agents that model collocated flocks of birds. Generic migratory corridors are suitably adapted to model migratory flyways for each waterfowl metapopulation. The resulting data is generated in XML format compatible with our simulation-based epidemiological analysis environment called SEARUMS. Case studies conducted using SEARUMS and the generated models for high-risk waterfowl species indicate good correlation between simulated and observed viral dispersion patterns, demonstrating the effectiveness of the proposed methodology.
Keywords: migratory flyways; tessalation; agent-based modelling; simulation; computational epidemiology; avian influenza; H5N1.
International Journal of Computer Aided Engineering and Technology, 2019 Vol.11 No.6, pp.747 - 762
Received: 14 Jan 2017
Accepted: 06 Jul 2017
Published online: 30 Sep 2019 *