Development and implementation of global animal disease surveillance has been limited by the lack of information systems that enable near real-time data capturing, sharing, analysis, and related decision- and policy-making. The objective of this paper is to describe requirements for global animal disease surveillance, including design and functionality of tools and methods for visualization and analysis of animal disease data. The paper also explores the potential application of techniques for spatial and spatio-temporal analysis on global animal disease surveillance, including for example, landscape genetics, social network analysis, and Bayesian modeling. Finally, highly pathogenic avian influenza data from Denmark and Sweden are used to illustrate the potential application of a novel system (Disease BioPortal) for data sharing, visualization, and analysis for regional and global surveillance efforts.
Bibliographical noteFunding Information:
This study was funded in part by grants from the U.S. National Center for Medical Intelligence, the U.S. Department of Agriculture, the University of California in Davis, the Kansas Bioscience Authority, and the U.S. Foreign Animal Disease Center – Department of Homeland Security under Grant Award Number 2010-ST-061-AG0002.
- Avian influenza
- Disease BioPortal
- Global animal disease surveillance