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Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms

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  • Tabassom Sedighi

    (Centre for Environmental and Agricultural Informatics, School of Water, Energy and Environment (SWEE), Cranfield University, Cranfield MK43 0AL, UK)

  • Liz Varga

    (Department of Civil, Environmental and Geomatic Engineering, Faculty of Engineering, UCL, London WC1E 6BT, UK)

Abstract

Controlling bovine tuberculosis (bTB) disease in cattle farms in England is seen as a challenge for farmers, animal health, environment and policy-makers. The difficulty in diagnosis and controlling bTB comes from a variety of factors: the lack of an accurate diagnostic test which is higher in specificity than the currently available skin test; isolation periods for purchased cattle; and the density of active badgers, especially in high-risk areas. In this paper, to enable the complex evaluation of bTB disease, a dynamic Bayesian network (DBN) is designed with the help of domain experts and available historical data. A significant advantage of this approach is that it represents bTB as a dynamic process that evolves periodically, capturing the actual experience of testing and infection over time. Moreover, the model demonstrates the influence of particular risk factors upon the risk of bTB breakdown in cattle farms.

Suggested Citation

  • Tabassom Sedighi & Liz Varga, 2021. "Evaluating the Bovine Tuberculosis Eradication Mechanism and Its Risk Factors in England’s Cattle Farms," IJERPH, MDPI, vol. 18(7), pages 1-24, March.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:7:p:3451-:d:524686
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    References listed on IDEAS

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    1. Christl A. Donnelly & Rosie Woodroffe & D. R. Cox & John Bourne & George Gettinby & Andrea M. Le Fevre & John P. McInerney & W. Ivan Morrison, 2003. "Impact of localized badger culling on tuberculosis incidence in British cattle," Nature, Nature, vol. 426(6968), pages 834-837, December.
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    Cited by:

    1. Tabassom Sedighi & Liz Varga & Amin Hosseinian-Far & Alireza Daneshkhah, 2021. "Economic Evaluation of Mental Health Effects of Flooding Using Bayesian Networks," IJERPH, MDPI, vol. 18(14), pages 1-16, July.

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