Location of Repository

Construction of networks with intrinsic temporal structure from UK cattle movement data

By M. Fred Heath, Matthew C. Vernon and Cerian R. Webb

Abstract

Background: The implementation of national systems for recording the movements of cattle between agricultural holdings in the UK has enabled the development and parameterisation of network-based models for disease spread. These data can be used to form a network in which each cattle-holding location is represented by a single node and links between nodes are formed if there\ud is a movement of cattle between them in the time period selected. However, this approach loses information on the time sequence of events thus reducing the accuracy of model predictions. In this paper, we propose an alternative way of structuring the data which retains information on the\ud sequence of events but which still enables analysis of the structure of the network. The fundamental feature of this network is that nodes are not individual cattle-holding locations but are instead direct movements between pairs of locations. Links are made between nodes when the second\ud node is a subsequent movement from the location that received the first movement.\ud Results: Two networks are constructed assuming (i) a 7-day and (ii) a 14-day infectious period using British Cattle Movement Service (BCMS) data from 2004 and 2005. During this time period there were 4,183,670 movements that could be derived from the database. In both networks over\ud 98% of the connected nodes formed a single giant weak component. Degree distributions show scale-free behaviour over a limited range only, due to the heterogeneity of locations: farms, markets, shows, abattoirs. Simulation of the spread of disease across the networks demonstrates\ud that this approach to restructuring the data enables efficient comparison of the impact of transmission rates on disease spread.\ud Conclusion: The redefinition of what constitutes a node has provided a means to simulate disease spread using all the information available in the BCMS database whilst providing a network that can be described analytically. This will enable the construction of generic networks with similar\ud properties with which to assess the impact of small changes in network structure on disease dynamics

Topics: SF, QL
Publisher: BioMed Central Ltd.
Year: 2008
OAI identifier: oai:wrap.warwick.ac.uk:528

Suggested articles

Preview

Citations

  1. (2004). A: Velocity and hierarchical spread of epidemic outbreaks in scale-free networks. Phys Rev Lett doi
  2. (2002). Barabási AL: Halting viruses in scale-free networks. doi
  3. (2005). Characteristics of cattle movements in Britain – an analysis of records from the Cattle Tracing System. Animal Science doi
  4. (1995). Concurrent partnerships and transmission dynamics in networks. doi
  5. (2007). Contagion: Free Software for Network Analysis & Generation, and Disease Simulation
  6. (2001). DJ: Random graphs with arbitrary degree distributions and their applications. Phys Rev E doi
  7. (1994). Faust K: Social Network Analysis. Methods and Applications Cambridge: doi
  8. Identifying and Tracking Livestock in England Report by the Comptroller and Auditor General. London: National Audit Office;
  9. (2006). Identifying temporal variation in reported births, deaths and movements of cattle in Britain.
  10. (2001). Infection dynamics on scale-free networks. doi
  11. Introduction to Graph Theory
  12. (2006). IZ: Demographic structure and pathogen dynamics on the network of livestock movements in Great Britain. Proc Biol Sci doi
  13. (1970). Leinhardt S: A method for detecting structure in sociometric data. doi
  14. (1996). Measures of concurrency in networks and the spread of infectious disease. doi
  15. (2007). Network analysis in public health: history, methods, and applications. Ann Rev Public Health doi
  16. (2005). NP: Network analysis of cattle movements in Great Britain.
  17. (2006). Review of the Livestock Movement Controls London: Department for Environment Food and Rural Affairs;
  18. RM: Infectious Diseases of Humans Oxford:
  19. (2006). RR: Infectious disease control using contact tracing in random and scale-free networks. doi
  20. (2006). RR: Modelling the initial spread of footand-mouth disease through animal movements. Proc Biol Sci
  21. (2001). UK foot and mouth epidemic: Stochastic dispersal in a heterogenous landscape. Science
  22. (2001). Vespignani A: Epidemic spreading in scalefree networks. doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.