Impact of Genetic Selection for Increased Cattle Resistance to Bovine Tuberculosis on Disease Transmission Dynamics

Abstract

Bovine tuberculosis (bTB) poses a challenge to animal health and welfare worldwide. Presence of genetic variation in host resistance to Mycobacterium bovis infection makes the trait amenable to improvement with genetic selection. Genetic evaluations for resistance to infection in dairy cattle are currently available in the United Kingdom (UK), enabling genetic selection of more resistant animals. However, the extent to which genetic 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 attempted to represent 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 modeled 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 <1% in 4, 5, 7, and 11 generations, respectively. Similarly, the proportion of long 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 suggest that genetic selection could be a viable tool that can complement existing management and surveillance methods to control and ultimately eradicate bTB.

Epidemiological Study of Mycobacterium bovis Infection in Buffalo and Cattle in Amazonas, Brazil

“…Statistical modeling studies are important to elucidate the transmission dynamics of BTB within and between herds (26)(27)(28)(29). Additionally, mathematical modeling studies have been carried out to analyze disease transmission and provide insight into useful control measures (30)(31)(32)(33).…”

Animal tuberculosis: impact of disease heterogeneity in transmission, diagnosis, and control

“…Besides, host social behaviour and genetics are also related to susceptibility to disease, and advances in disease control can be achieved by selective breeding programmes. In a work performed by Raphaka et al (2018), the contribution of genetic selection for TB eradication was assessed in the UK, and genetic selection was associated with a reduction of TB breakdowns severity over generations (Raphaka et al, 2018). It is important to note that this option is a long‐term control measure that should be complemented with other management and surveillance approaches.…”

Breeding strategies for animal resilience to weather variation in meat sheep

“…True breeding values of an individual (TBV) and environmental deviations (ENV) in generation zero (i.e. before genetic selection) were simulated for each trait from multivariate normal distributions TBV~(0, G 0 ) and ENV~(0, E), where G 0 and E are the genetic and residual variance-covariance matrices for the simulated traits, respectively [24,25]. All matrices were examined to ensure they were positive-definite.…”

“…Twenty (20) non-overlapping generations were simulated by selecting the best males (30%) and females (50%) in each generation and mating them randomly to produce offspring. The TBVs of the offspring were calculated as TBV offspring = 0.5(TBV sire + TBV dam ) + MS TBV , where MS TBV represents the Mendelian sampling terms derived for each trait from a multivariate normal distribution MS TBV~( 0, 0.5G 0 (1-F )), with G 0 corresponding to the genetic variance-covariance matrix in generation zero and F was the average pedigree inbreeding coefficient of the parents [24,25]. Environmental deviations for the offspring were computed from the multivariate normal distribution described above.…”