Topographic determinants of foot and mouth disease transmission in the UK 2001 epidemic

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• 作者：Nicholas J Savill (1) (2)
  Darren J Shaw (3)
  Rob Deardon (1) (7)
  Michael J Tildesley (4)
  Matthew J Keeling (4)
  Mark EJ Woolhouse (2)
  Stephen P Brooks (1)
  Bryan T Grenfell (5) (6)
  
• 刊名：BMC Veterinary Research
• 出版年：2006
• 出版时间：December 2006
• 年：2006
• 卷：2
• 期：1
• 全文大小：3385KB
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• 作者单位：Nicholas J Savill (1) (2)
  Darren J Shaw (3)
  Rob Deardon (1) (7)
  Michael J Tildesley (4)
  Matthew J Keeling (4)
  Mark EJ Woolhouse (2)
  Stephen P Brooks (1)
  Bryan T Grenfell (5) (6)
  
  1. Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WB, UK
  2. Institute of Infection and Immunology Research, School of Biological Sciences, University of Edinburgh, Kings Buildings, West Mains Road, EH9 3JT, Edinburgh, UK
  3. Veterinary Clinical Studies, R(D)SVS, University of Edinburgh, Easter Bush Veterinary Centre, EH25 9RG, Roslin, Midlothian, UK
  7. Cambridge Infectious Diseases Consortium, Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge, CB3 0ES, UK
  4. Ecology and Epidemiology Group, Department of Biological Sciences, University of Warwick, Gibbet Hill Road, CV4 7AL, Coventry, UK
  5. Center for Infectious Disease Dynamics, Department of Entomology and Biology, Pennsylvania State University, 16802, University Park, PA, USA
  6. Fogarty International Center, National Institutes of Health, 20892, Bethesda, MD, USA
  

文摘

Background A key challenge for modelling infectious disease dynamics is to understand the spatial spread of infection in real landscapes. This ideally requires a parallel record of spatial epidemic spread and a detailed map of susceptible host density along with relevant transport links and geographical features. Results Here we analyse the most detailed such data to date arising from the UK 2001 foot and mouth epidemic. We show that Euclidean distance between infectious and susceptible premises is a better predictor of transmission risk than shortest and quickest routes via road, except where major geographical features intervene. Conclusion Thus, a simple spatial transmission kernel based on Euclidean distance suffices in most regions, probably reflecting the multiplicity of transmission routes during the epidemic.