The role of movement restrictions in limiting the economic impact of livestock infections

Abstract

Livestock movements are essential for the economic success of the industry. However, these movements come with the risk of long-range spread of infection, potentially bringing infection to previously disease-free areas where subsequent localized transmission can be devastating. Mechanistic predictive models usually consider controls that minimize the number of livestock affected without considering other costs of an ongoing epidemic. However, it is more appropriate to consider the economic burden, as movement restrictions have major consequences for the economic revenue of farms. Here, using mechanistic models of foot-and-mouth disease, bluetongue virus and bovine tuberculosis in the UK, we compare the economically optimal control strategies for these diseases. We show that for foot-and-mouth disease, the optimal strategy is to ban movements in a small radius around infected farms; the balance between disease control and maintaining ‘business as usual’ varies between regions. For bluetongue virus and bovine tuberculosis, we find that the cost of any movement ban is greater than the epidemiological benefits due to the low within-farm prevalence and slow rate of disease spread. This work suggests that movement controls need to be carefully matched to the epidemiological and economic consequences of the disease, and that optimal movement bans are often of far shorter duration than allowed under existing policy.

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Fig. 1: Impact of movement bans on the cost of livestock infectious diseases.

Data availability

The raw simulation data used to create Fig. 1 in the main text and all figures in the Supplementary Information are available from corresponding author M.J.T. on request. The authors do not have permission to share the farm-level data for the UK. However, the demographic data that includes farm locations, farm sizes and species composition, as well as the data on livestock movements between farms can be accessed via the RADAR system (e-mail: RADAR@apha.gsi.gov.uk).

Code availability

The code used to create and analyse the raw data and produce the figures are available from the corresponding author on request. The code for the simulation models can be accessed by contacting the following contributing authors: the foot-and-mouth disease model, M.J.T.; the bluetongue virus model, S.B. and the bovine tuberculosis model E.B.P.

References

  1. 1.

    Gibbens, J. C. et al. Descriptive epidemiology of the 2001 foot-and-mouth disease epidemic in Great Britain: the first five months. Vet. Rec. 149, 729–743 (2001).

    CAS  Article  Google Scholar 

  2. 2.

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

    CAS  Article  Google Scholar 

  3. 3.

    Ferguson, N. M., Donnelly, C. A. & Anderson, R. M. The foot-and-mouth epidemic in Great Britain: pattern of spread and impact of interventions. Science 292, 1155–1160 (2001).

    CAS  Article  Google Scholar 

  4. 4.

    Saegerman, C., Berkvens, D. & Mellor, P. S. Bluetongue epidemiology in the European Union. Emerging infectious diseases. Natl Cent. Infect. Dis. 14, 539–544 (2008).

    Google Scholar 

  5. 5.

    Mercier, A. et al. Spread rate of lumpy skin disease in the Balkans, 2015–16. Transbound. Emerg. Dis. 65, 240–243 (2018).

    CAS  Article  Google Scholar 

  6. 6.

    Tasioudi, K. E. et al. Emergence of lumpy skin disease in Greece, 2015. Transbound. Emerg. Dis. 63, 260–265 (2016).

    CAS  Article  Google Scholar 

  7. 7.

    Docuel, V. et al. Epidemiology, molecular virology and diagnostics of Schmallenberg virus, an emerging orthobunyavirus in Europe. Vet. Res. 44, 31 (2013).

    Article  Google Scholar 

  8. 8.

    Hoffmann, B. et al. Novel orthobunyavirus in cattle, Europe, 2011. Emerg. Infect. Dis. 18, 469–472 (2012).

    Article  Google Scholar 

  9. 9.

    Green, L. E. & George, T. R. N. Assessment of current knowledge of footrot in sheep with particular reference to Dichelobacter nodosus and implications for elimination or control strategies for sheep in Great Britain. Vet. J. 175, 173–180 (2008).

    CAS  Article  Google Scholar 

  10. 10.

    Baylis, M. & McIntyre, K. M. Scrapie control under new strain. Nature 432, 810–811 (2004).

    CAS  Article  Google Scholar 

  11. 11.

    Schiller, I. et al. Bovine tuberculosis: a review of current and emerging diagnostic techniques in view of their relevance for disease control and eradication. Transbound. Emerg. Dis. 57, 205–220 (2010).

    CAS  Google Scholar 

  12. 12.

    Brooks Pollock, E., Roberts, G. O. & Keeling, M. J. A dynamic model of bovine tuberculosis spread and control in Great Britain. Nature 511, 228–231 (2014).

    CAS  Article  Google Scholar 

  13. 13.

    Garcia-Alvarez, L., Webb, C. R. & Holmes, M. A. A novel field-based approach to validate the use of network models for disease spread between dairy herds. Epidemiol. Infect. 139, 1863–1874 (2011).

    CAS  Article  Google Scholar 

  14. 14.

    Kiss, I. Z., Green, D. M. & Kao, R. R. The effect of network mixing patterns on epidemic dynamics and the efficacy of disease contact tracing. J. Roy. Soc. Interface 5, 791–799 (2008).

    Article  Google Scholar 

  15. 15.

    Contingency Plan for Exotic Notifiable Diseases of Animals in England (DEFRA, 2017); https://www.gov.uk/government/publications/contingency-plan-for-exotic-notifiable-diseases-of-animals-in-england

  16. 16.

    Thompson, D. et al. Economic costs of the foot and mouth disease outbreak in the United Kingdom in 2001. Rev. Sci. Tech. 21, 675–687 (2002).

    CAS  Article  Google Scholar 

  17. 17.

    Elbers, A. et al. Field observations during the bluetongue serotype 8 epidemic in 2006: I. Detection of first outbreaks and clinical signs in sheep and cattle in Belgium, France and the Netherlands. Prev. Vet. Med. 87, 21–30 (2008).

    Article  Google Scholar 

  18. 18.

    Krebs, J. R. et al. Bovine Tuberculosis in Cattle and Badgers (Ministry of Agriculture, Fisheries and Food, 1997); http://www.bovinetb.info/docs/krebs.pdf

  19. 19.

    Donnelly, C. A. & Nouvellet, P. The contribution of badgers to confirmed tuberculosis in cattle in high-incidence areas in England. PLoS Curr. 1, 097a904d3f3619db2fe78d24bc776098 (2013).

    Google Scholar 

  20. 20.

    Inamura M., Rushton J. & Antón J. Risk Management of Outbreaks of Livestock Diseases OECD Food, Agriculture and Fisheries Papers No. 91 (OECD, 2015).

  21. 21.

    Yang, P. C., Chu, R. M., Chung, W. B. & Sung, H. T. Epidemiological characteristics and financial costs of the 1997 foot-and-mouth disease epidemic in Taiwan. Vet. Rec. 145, 731–734 (1999).

    CAS  Article  Google Scholar 

  22. 22.

    Bicknell, K. B., Wilen, J. E. & Howitt, R. E. Public policy and private incentives for livestock disease control. Aust. J. Agric. Resour. Econ. 43, 501–521 (2002).

    Article  Google Scholar 

  23. 23.

    Epanchin-Niell, R. S. & Wilen, J. E. Optimal spatial control of biological invasions. J. Environ. Econ. Manag. 63, 260–270 (2012).

    Article  Google Scholar 

  24. 24.

    Olson, L. J. & Roy, S. Controlling a biological invasion: a non-classical dynamic economic model. Econ. Theory 36, 453–469 (2008).

    Article  Google Scholar 

  25. 25.

    Probert, W. J. M. et al. Real-time decision-making during emergency disease outbreaks. PLoS Comput. Biol. 14, e1006202 (2018).

    Article  Google Scholar 

  26. 26.

    Feng, S., Patton, M. & Davis, J. Market impact of foot-and-mouth disease control strategies: a UK case study. Front. Vet. Sci. 4, 129 (2017).

    Article  Google Scholar 

  27. 27.

    Rich, K. M. & Winter-Nelson, A. An integrated epidemiological-economic analysis of foot and mouth disease: applications to the southern cone of South America. Am. J. Agric. Econ. 89, 682–697 (2007).

    Article  Google Scholar 

  28. 28.

    Longworth, N., Mourits, M. C. & Saatkamp, H. W. Economic analysis of HPAI control in the Netherlands II: comparison of control strategies. Transbound. Emerg. Dis. 61, 217–232 (2014).

    CAS  Article  Google Scholar 

  29. 29.

    Rich, K. M. & Wanyoike, F. An assessment of the regional and national socio-economic impacts of the 2007 Rift Valley fever outbreak in Kenya. Am. J. Trop. Med. Hyg. 83(2 Suppl), 52–57 (2017).

    Google Scholar 

  30. 30.

    Tildesley, M. J. et al. Optimal reactive vaccination strategies for a foot-and-mouth outbreak in the UK. Nature 440, 83–86 (2016).

    Article  Google Scholar 

  31. 31.

    Brand, S. P. C. & Keeling, M. J. The impact of temperature changes on vector-borne disease transmission: Culicoides midges and bluetongue virus. J. R. Soc. Interface 14, 20160481 (2017).

    Article  Google Scholar 

  32. 32.

    Woolhouse, M. et al. Epidemiology. Foot-and-mouth disease under control in the UK. Nature 411, 258–259 (2001).

    CAS  Article  Google Scholar 

  33. 33.

    Sumner, T., Orton, R. J., Green, D. M., Kao, R. R. & Gubbins, S. Quantifying the roles of host movement and vector dispersal in the transmission of vector-borne diseases of livestock. PLoS Comput. Biol. 13, e1005470–22 (2017).

    Article  Google Scholar 

  34. 34.

    Casey-Bryars, M. et al. Waves of endemic foot-and-mouth disease in eastern Africa suggest feasibility of proactive vaccination approaches. Nat. Ecol. Evol. 2, 1449–1457 (2018).

    Article  Google Scholar 

  35. 35.

    Anderson, I. Foot & Mouth Disease 2001: Lessons to be Learned Inquiry Report (The Stationary Office, 2002).

  36. 36.

    Gunn, G. et al. Assessing the Economic Impact of Different Bluetongue Virus (BTV) Incursion Scenarios in Scotland (Scottish Government, 2008).

  37. 37.

    Measures to Address Bovine TB in Badgers (DEFRA, 2011); https://www.gov.uk/government/publications/measures-to-address-bovine-tuberculosis-in-badgers-impact-assessment

  38. 38.

    Diggle, P. Spatio-temporal point processes, partial likelihood, foot and mouth disease. Stat. Methods Med. Res. 15, 325–336 (2006).

    Article  Google Scholar 

  39. 39.

    Tildesley, M. J. et al. Accuracy of models for the 2001 UK foot-and-mouth epidemic. Proc. R. Soc. B 275, 1459–1468 (2008).

    Article  Google Scholar 

  40. 40.

    Deardon, R. et al. Inference for individual-level models of infectious diseases in large populations. Stat. Sin. 20, 239–261 (2010).

    Google Scholar 

  41. 41.

    Jewell, C. P., Kypraios, T., Neal, P. & Roberts, G. O. Bayesian analysis for emerging infectious diseases. Bayesian Anal. 4, 465–496 (2009).

    Article  Google Scholar 

  42. 42.

    Kao, R. R., Danon, L., Green, D. M. & Kiss, I. Z. Demographic structure and pathogen dynamics on the network of livestock movements in Great Britain. Proc. R. Soc. B 273, 1999–2007 (2006).

    CAS  Article  Google Scholar 

  43. 43.

    Green, D. M., Kiss, I. Z. & Kao, R. R. Modelling the initial spread of foot-and-mouth disease through animal movements. Proc. R. Soc. B 273, 2729–2735 (2006).

    CAS  Article  Google Scholar 

  44. 44.

    Dawson, P. M., Werkman, M., Brooks Pollock, E. & Tildesley, M. J. Epidemic predictions in an imperfect world: modelling disease spread with partial data. Proc. R. Soc. B 282, 20150205 (2015).

    Article  Google Scholar 

  45. 45.

    Szmaragd, C. et al. A modeling framework to describe the transmission of bluetongue virus within and between farms in Great Britain. PLoS ONE 4, e7741 (2009).

    Article  Google Scholar 

  46. 46.

    Turner, J., Bowers, R. G. & Baylis, M. Modelling bluetongue virus transmission between farms using animal and vector movements. Sci. Rep. 2, 319 (2012).

    Article  Google Scholar 

  47. 47.

    Græsbøll, K., Bødker, R., Enøe, C. & Christiansen, L. E. Simulating spread of bluetongue virus by flying vectors between hosts on pasture. Sci. Rep. 2, 863 (2012).

    Article  Google Scholar 

  48. 48.

    Gubbins, S., Carpenter, S., Baylis, M., Wood, J. L. N. & Mellor, P. S. Assessing the risk of bluetongue to UK livestock: uncertainty and sensitivity analyses of a temperature-dependent model for the basic reproduction number. J. R. Soc. Interface 5, 363–371 (2008).

    Article  Google Scholar 

  49. 49.

    United Kingdom Climate Projections (UKCP09) (Met Office, 2009); https://www.metoffice.gov.uk/climatechange/science/monitoring/ukcp09/

  50. 50.

    Carpenter, S. et al. Temperature dependence of the extrinsic incubation period of orbiviruses in culicoides biting midges. PLoS ONE 6, e27987 (2011).

    CAS  Article  Google Scholar 

  51. 51.

    Sanders, C. J. et al. Influence of season and meteorological parameters on flight activity of Culicoides biting midges. J. Appl. Ecol. 48, 1355–1364 (2011).

    Article  Google Scholar 

  52. 52.

    Kettle, D. S. The bionomics and control of Culicoides and Leptoconops (Diptera, Ceratopogonidae = Heleidae). Annu. Rev. Entomol. 7, 401–418 (1962).

    Article  Google Scholar 

  53. 53.

    Mellor, P. S., Boorman, J. & Baylis, M. Culicoides biting midges: their role as arbovirus vectors. Annu. Rev. Entomol. 45, 307–340 (2000).

    CAS  Article  Google Scholar 

  54. 54.

    UK Bluetongue Control Strategy (DEFRA, 2008); https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/343741/bluetongue-control-strategy081201.pdf

  55. 55.

    Karolemeas, K. et al. Estimation of the relative sensitivity of the comparative tuberculin skin test in tuberculous cattle herds subjected to depopulation. PLoS ONE 7, e43217 (2012).

    CAS  Article  Google Scholar 

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Acknowledgements

M.J.T. and M.J.K. acknowledge support from the Biotechnology and Biological Sciences Research Council (grant number BB/K010972/4). We thank M. Ferrari and W. Probert for useful discussions regarding this manuscript.

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Contributions

M.J.T., S.B., E.B.P. and M.W. carried out simulations using the three livestock disease models. N.V.B. developed the Shiny app for visualization of sensitivity analysis. M.J.K. and M.J.T. analysed the outputs of the simulation models. M.J.K. led the sensitivity analysis of the modelling results and provided intellectual expertise on all three livestock disease models. All authors contributed to the writing of this manuscript.

Corresponding authors

Correspondence to M. J. Tildesley or S. Brand or E. Brooks Pollock.

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The authors declare no competing interests.

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Supplementary Information

Supplementary notes, Supplementary Tables 1–4, Supplementary Figs. 1–4 and Supplementary references 1–37.

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Tildesley, M.J., Brand, S., Brooks Pollock, E. et al. The role of movement restrictions in limiting the economic impact of livestock infections. Nat Sustain 2, 834–840 (2019). https://doi.org/10.1038/s41893-019-0356-5

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