Impact of genetic selection for increased cattle resistance to bovine tuberculosis on disease transmission dynamics

K Raphaka, E Sanchez-Molano, S Tsairidou, O Anacleto, EJ Glass, JA Woolliams, A Doeschl-Wilson, G Banos

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Abstract

Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to bTB infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to bTB in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent genetic to which selection could contribute to bTB eradication is unknown. The objective of this study was to quantify the impact of genetic selection for bTB resistance on cattle-to-cattle disease transmission dynamics and prevalence by developing a stochastic genetic epidemiological model. The model was used to implement genetic selection in a simulated cattle population. The model considered various levels of selection intensity over 20 generations assuming genetic heterogeneity in host resistance to infection. Our model mimicked the dairy cattle population structure and current bTB control strategies in the UK, and was informed by genetic and epidemiological parameters inferred from data collected from UK bTB infected dairy herds. The risk of a bTB breakdown was modelled as the percentage of herds where initially infected cows (index cases) generated secondary cases by infecting herd-mates. The model predicted that this risk would be reduced by half after 4, 6, 9 and 15 generations for selection intensities corresponding to genetic selection of the 10, 25, 50 and 70% most resistant sires, respectively. In herds undergoing bTB breakdowns, genetic selection reduced the severity of breakdowns over generations by reducing both the percentage of secondary cases and the duration over which new secondary cases were detected. Selection of the 10, 25, 50 and 70% most resistant sires reduced the percentage of secondary cases to less than 1% in 4, 5, 7 and 11 generations, respectively. Similarly, the proportion of chronic breakdowns (breakdowns in which secondary cases were detected for more than 365 days) was reduced by half in 2, 2, 3 and 4 generations, respectively. Collectively, results confirm that genetic selection is a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.
Original languageEnglish
Article number237
Number of pages14
JournalFrontiers in Veterinary Science
Volume5
Early online date1 Oct 2018
DOIs
Publication statusFirst published - 1 Oct 2018

Fingerprint

bovine tuberculosis
disease transmission
cattle
United Kingdom
selection intensity
herds
sires
dairy cattle
cattle diseases
dairy herds
animal health
infection
animal welfare
complement
population structure
cows

Keywords

  • Bovine tuberculosis
  • Epidemiological model
  • Genetic selection
  • Prevalence
  • Resistance
  • Susceptibility

Cite this

Raphaka, K ; Sanchez-Molano, E ; Tsairidou, S ; Anacleto, O ; Glass, EJ ; Woolliams, JA ; Doeschl-Wilson, A ; Banos, G. / Impact of genetic selection for increased cattle resistance to bovine tuberculosis on disease transmission dynamics. In: Frontiers in Veterinary Science. 2018 ; Vol. 5.
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abstract = "Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to bTB infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to bTB in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent genetic to which selection could contribute to bTB eradication is unknown. The objective of this study was to quantify the impact of genetic selection for bTB resistance on cattle-to-cattle disease transmission dynamics and prevalence by developing a stochastic genetic epidemiological model. The model was used to implement genetic selection in a simulated cattle population. The model considered various levels of selection intensity over 20 generations assuming genetic heterogeneity in host resistance to infection. Our model mimicked the dairy cattle population structure and current bTB control strategies in the UK, and was informed by genetic and epidemiological parameters inferred from data collected from UK bTB infected dairy herds. The risk of a bTB breakdown was modelled as the percentage of herds where initially infected cows (index cases) generated secondary cases by infecting herd-mates. The model predicted that this risk would be reduced by half after 4, 6, 9 and 15 generations for selection intensities corresponding to genetic selection of the 10, 25, 50 and 70{\%} most resistant sires, respectively. In herds undergoing bTB breakdowns, genetic selection reduced the severity of breakdowns over generations by reducing both the percentage of secondary cases and the duration over which new secondary cases were detected. Selection of the 10, 25, 50 and 70{\%} most resistant sires reduced the percentage of secondary cases to less than 1{\%} in 4, 5, 7 and 11 generations, respectively. Similarly, the proportion of chronic breakdowns (breakdowns in which secondary cases were detected for more than 365 days) was reduced by half in 2, 2, 3 and 4 generations, respectively. Collectively, results confirm that genetic selection is a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.",
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Impact of genetic selection for increased cattle resistance to bovine tuberculosis on disease transmission dynamics. / Raphaka, K; Sanchez-Molano, E; Tsairidou, S; Anacleto, O; Glass, EJ; Woolliams, JA; Doeschl-Wilson, A; Banos, G.

In: Frontiers in Veterinary Science, Vol. 5, 237, 01.10.2018.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Raphaka, K

AU - Sanchez-Molano, E

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AB - Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to bTB infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to bTB in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent genetic to which selection could contribute to bTB eradication is unknown. The objective of this study was to quantify the impact of genetic selection for bTB resistance on cattle-to-cattle disease transmission dynamics and prevalence by developing a stochastic genetic epidemiological model. The model was used to implement genetic selection in a simulated cattle population. The model considered various levels of selection intensity over 20 generations assuming genetic heterogeneity in host resistance to infection. Our model mimicked the dairy cattle population structure and current bTB control strategies in the UK, and was informed by genetic and epidemiological parameters inferred from data collected from UK bTB infected dairy herds. The risk of a bTB breakdown was modelled as the percentage of herds where initially infected cows (index cases) generated secondary cases by infecting herd-mates. The model predicted that this risk would be reduced by half after 4, 6, 9 and 15 generations for selection intensities corresponding to genetic selection of the 10, 25, 50 and 70% most resistant sires, respectively. In herds undergoing bTB breakdowns, genetic selection reduced the severity of breakdowns over generations by reducing both the percentage of secondary cases and the duration over which new secondary cases were detected. Selection of the 10, 25, 50 and 70% most resistant sires reduced the percentage of secondary cases to less than 1% in 4, 5, 7 and 11 generations, respectively. Similarly, the proportion of chronic breakdowns (breakdowns in which secondary cases were detected for more than 365 days) was reduced by half in 2, 2, 3 and 4 generations, respectively. Collectively, results confirm that genetic selection is a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.

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