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

Nature Sustainability volume 2, pages 834–840 (2019)Cite this article

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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.

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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.

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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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Authors and Affiliations

  1. Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, Coventry, UK

    M. J. Tildesley, S. Brand, N. V. Bradbury & M. J Keeling

  2. Bristol Veterinary School, University of Bristol, Bristol, UK

    E. Brooks Pollock

  3. London Centre for Neglected Tropical Disease Research, Department of Infectious Disease Epidemiology, Imperial College London, London, UK

    M. Werkman

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  1. M. J. Tildesley
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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.

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Correspondence to M. J. Tildesley, 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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