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A dynamic model of bovine tuberculosis spread and control in Great Britain

Nature volume 511, pages 228231 (10 July 2014) | Download Citation


Bovine tuberculosis (TB) is one of the most complex, persistent and controversial problems facing the British cattle industry, costing the country an estimated £100 million per year1. The low sensitivity of the standard diagnostic test leads to considerable ambiguity in determining the main transmission routes of infection, which exacerbates the continuing scientific debate2,3,4,5,6. In turn this uncertainty fuels the fierce public and political disputes on the necessity of controlling badgers to limit the spread of infection. Here we present a dynamic stochastic spatial model for bovine TB in Great Britain that combines within-farm and between-farm transmission. At the farm scale the model incorporates stochastic transmission of infection, maintenance of infection in the environment and a testing protocol that mimics historical government policy. Between-farm transmission has a short-range environmental component and is explicitly driven by movements of individual cattle between farms, as recorded in the Cattle Tracing System2. The resultant model replicates the observed annual increase of infection over time as well as the spread of infection into new areas. Given that our model is mechanistic, it can ascribe transmission pathways to each new case; the majority of newly detected cases involve several transmission routes with moving infected cattle, reinfection from an environmental reservoir and poor sensitivity of the diagnostic test all having substantive roles. This underpins our findings on the implications of control measures. Very few of the control options tested have the potential to reverse the observed annual increase, with only intensive strategies such as whole-herd culling or additional national testing proving highly effective, whereas controls focused on a single transmission route are unlikely to be highly effective.

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  1. 1.

    Department for Environment Food and Rural Affairs. Bovine Tuberculosis Evidence Plan (2013)

  2. 2.

    National Audit Office. Identifying and Tracking Livestock in England (2003)

  3. 3.

    To stamp out “so terrible a malady”: bovine tuberculosis and tuberculin testing in Britain, 1890–1939. Med. Hist. 48, 29–48 (2004)

  4. 4.

    A review of tuberculosis science and policy in Great Britain. Vet. Microbiol. 112, 119–126 (2006)

  5. 5.

    The Independent Scientific Review Group. Bovine Tuberculosis in Cattle and Badgers (1997)

  6. 6.

    , , , & Introduction of bovine tuberculosis to north-east England by bought-in cattle. Vet. Rec. 159, 265–271 (2006)

  7. 7.

    The Independent Scientific Group on Cattle TB. Bovine TB: The Scientific Evidence (2007)

  8. 8.

    Department for Environment Food and Rural Affairs. Bovine TB Eradication Programme for England (2011)

  9. 9.

    et al. Immune responses in bovine tuberculosis. Tuberculosis (Edinb.) 81, 103–107 (2001)

  10. 10.

    & Investigations of cattle herd breakdowns with bovine tuberculosis in four counties of England and Wales using VETNET data. Prev. Vet. Med. 70, 293–311 (2005)

  11. 11.

    , , , & The tuberculin test. Vet. Microbiol. 40, 111–124 (1994)

  12. 12.

    et al. Estimating the hidden burden of bovine tuberculosis in Great Britain. PLOS Comput. Biol. 8, e1002730 (2012)

  13. 13.

    et al. Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape. Science 294, 813–817 (2001)

  14. 14.

    , & The foot-and-mouth epidemic in Great Britain: pattern of spread and impact of interventions. Science 292, 1155–1160 (2001)

  15. 15.

    , , , & A simulation model for the spread of bovine tuberculosis within New Zealand cattle herds. Prev. Vet. Med. 32, 57–75 (1997)

  16. 16.

    , , , & Evaluation of surveillance strategies for bovine tuberculosis (Mycobacterium bovis) using an individual based epidemiological model. Prev. Vet. Med. 67, 283–301 (2005)

  17. 17.

    et al. Epidemiological implications of the contact network structure for cattle farms and the 20–80 rule. Biol. Lett. 1, 350–352 (2005)

  18. 18.

    , , & Estimates for local and movement-based transmission of bovine tuberculosis in British cattle. Proc. R. Soc. B 275, 1001–1005 (2008)

  19. 19.

    et al. The intrinsic transmission dynamics of tuberculosis epidemics. Nature Med. 1, 815–821 (1995)

  20. 20.

    et al. Simple model for tuberculosis in cattle and badgers. Proc. Natl Acad. Sci. USA 102, 17588–17593 (2005)

  21. 21.

    et al. Age-dependent patterns of bovine tuberculosis in cattle. Vet. Res. 44, 97 (2013)

  22. 22.

    , , & Estimating epidemiological parameters for bovine tuberculosis in British cattle using a Bayesian partial-likelihood approach. Proc. R. Soc. B 281, 20140248 (2014)

  23. 23.

    , & Sequential Monte Carlo without likelihoods. Proc. Natl Acad. Sci. USA 104, 1760–1765 (2007)

  24. 24.

    , , , & Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. J. R. Soc. Interface 6, 187–202 (2009)

  25. 25.

    & Is there an association between levels of bovine tuberculosis in cattle herds and badgers? Stat. Commun. Infect. Dis. 2, (2010)

  26. 26.

    et al. A restatement of the natural science evidence base relevant to the control of bovine tuberculosis in Great Britain. Proc. R. Soc. B 280, 20131634 (2013)

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This work was funded by BBSRC, the Wellcome Trust and EPSRC. We would like to thank G. Medley, L. Green, O. Courtenay, A. Ramirez-Villaescusa, J. Wood and L. Danon for helpful discussions on bovine TB dynamics. Thanks to A. Conlan and T. J. McKinley for advice on implementing SMC-ABC and to A. Conlan to setting up the Marx Bros cluster. The breakdown and reactor data was supplied by the AHVLA team (particularly A. Mitchell and R. Blackwell), the RADAR team and DEFRA.

Author information


  1. Disease Dynamics Unit, Department of Veterinary Medicine, University of Cambridge, Madingley Road, Cambridge CB3 0ES, UK

    • Ellen Brooks-Pollock
  2. WIDER Centre, Mathematics Institute and School of Life Sciences, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK

    • Ellen Brooks-Pollock
    •  & Matt J. Keeling
  3. Department of Statistics, University of Warwick, Gibbet Hill Road, Coventry CV4 7AL, UK

    • Gareth O. Roberts


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M.J.K. and E.B.-P. developed the model structure; E.B.-P. and G.O.R. developed the statistical methodology; all authors contributed to the writing of the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Matt J. Keeling.

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