Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system.
Crispell, J., Benton, C. H., Balaz, D., De Maio, N., Akhmetova, A., Allen, A., Biek, R., Breadon, E. L., Dale, J., Hewinson, G., Lycett, S. J., Nunez-Garcia, J., Skuce, R. A., Trewby, H., Wilson, D. J., Zadoks, R. N., Delahay, R. J. and R. R. Kao (2019)
eLife 8: e45833 (pdf)
Quantifying pathogen transmission in multi-host systems is difficult, as exemplified in bovine tuberculosis (bTB) systems, but crucial for disease control. The agent of bTB, Mycobacterium bovis, persists in cattle populations around the world, often where potential wildlife reservoirs are present. However, the relative contribution of different host species to bTB persistence is generally unknown. In the United Kingdom, the role of badgers in the persistence of infection in cattle is highly contentious, despite decades of research and control efforts. Here, we apply Bayesian phylogenetic and machine-learning approaches to bacterial genome data to quantify the role of badgers and cattle in M. bovis infection dynamics in an endemic area. Our results are consistent with a maintenance role of the sampled badger population and if representative, suggest control operations targeting cattle and badgers simultaneously are required. In addition, we provide the first directional estimates of inter-species transmission rates for M. bovis, which estimated badger-to-cattle transmission occurred 9.8 times more frequently than cattle-to-badger transmission, on average, in the sampled system.