Conlan, Andrew JK

Wood, James LN

English

Apollo (Cambridge)

Guest EditorialTesting the dairy differenceIn this issue Downs et al. present evidence for systematic differences in the performance of diagnostic tests for bovine tuberculosis (bTB) with respect to breed and production type (Downs et al., 2016). They explore how different diagnostic tests perform compared to post-mortem confirmation (PMC), finding that dairy animals are more likely to react to antemortem tests but that non-dairy “reactor” animals are more likely to have lesions detected. bTB in Great Britain (GB) is subject to an intensive control regime based on routine and targeted surveillance of cattle herds and removal of test positive animals. Systematic differences in diagnostic performance are critically important as, to a great extent, the statutory system is oriented around detecting reaction to tuberculin. However, the consequences of these observations are difficult to interpret due to the lack of a gold standard test for bTB infection and the feedback loop generated by the link between test frequency and test status within the statutory GB testing system (the more you test, the more you will find).bTB continues to spread in Great Britain, both in terms of the geographic range, and incidence (“Latest statistics on tuberculosis (TB) in cattle in Great Britain - Publications - GOV.UK,” n.d.), in the face of intensifying cattle controls. Reservoirs of infection within badger populations are undoubtedly contributing to this failure in some areas. However badger populations and their infections are essentially unmonitored, so the nature and magnitude of this contribution is uncertain (Brooks-Pollock and Wood, 2015) and far too open to debate (Grant, 2009). The impact of badger controls through either vaccination or culling is filtered through the lens of the cattle surveillance system and indirectly measured against their impact on incidence within cattle. As a consequence, the performance of diagnostic tests is of fundamental importance to improving cattle controls and also to understanding the wider patterns of transmission of M. bovis. In Britain today, symptomatic infection of M. bovis in cattle is rare, so the only measure of disease is PMC through gross visible lesions, identification of distinctive histopathology or culture of M. bovis. PMC from these measures is an imperfect diagnostic test with a low sensitivity, which depends on the time from infection. However, textbook views of progression with age are at odds with the higher risk of PMC in calves reported (Downs et al., 2016) (Brooks-Pollock et al., 2013), demonstrating the importance of other sources of variability, including susceptibility, immunity or routes of transmission. The limitations of PMC as a gold standard complicate the interpretation of these findings. The lower rate of PMC in dairy animals could be a result of the antemortem tests being more sensitive – and detecting infection at an earlier stage than can be confirmed easily. Alternatively, antemortem tests could be less specific and pulling out a higher rate of false positive animals. This distinction has important knock on effects for the risk of persistence of infection within herds and the impact of testing on farmers.Any positive test result for bTB results in removal of official-TB free status from a herd that can only be cleared by repeated testing of the whole herd. A lower test specificity in dairy herds would result in the restriction of herds clear of infection. Conversely, if dairy animals were being detected an earlier stage of infection and then lesions not found at post-mortem, some dairy herds will be escaping additional tests under more severe interpretation.The practical impact on control in these scenarios will be mitigated by the dynamic nature of testing in GB. If test specificity is lower in dairy herds, breakdowns would be more common – but resolve faster. Dairy herds have an increased risk of breakdown (Skuce et al., 2012), but PMC itself, along with herd size and the number of bought cattle are the only clear risk factors for breakdown duration at the national level (Karolemeas et al., 2010). Alternatively, if antemortem tests are more sensitive in dairy herds, the reduced intensity of testing resulting from failure to confirm animals at an early stage of infection could increase the chance of infection persisting in herds. However, this risk would be offset against the reduced time that infected animals are residing in herds and contributing to transmission. Breakdowns in this scenario would not necessarily be shorter if the rate of infection within the herd is high enough to generate new reactors. Transmission within dairy herds is genuinely likely greater than in other production types. Herds are typically larger and transmission rates scale are likely to scale with herd size (Conlan et al., 2012). However, the extent to which the association between dairy herds and infection is confounded by the strong correlation between herd size and other explanatory variables, including production type, is unclear. Less equivocally,  dairy herds typically retain animals for longer periods than other production types, increasing opportunities for transmission (Conlan et al., 2015). While Downs et al. adjust for herd size and background prevalence (assessed by testing interval) they do not account for differences in residence time and thus the potential for within-herd transmission and their age adjustment is somewhat simplistic. Thus, if the specificity of tuberculin testing is indeed lower in dairy herds, it may well be due to the greater exposure to M. bovis, if not necessarily transmission. So, how could these competing hypotheses be resolved? This study provides further evidence to suggest that the IFN- ESAT-6/CFP10 blood test has a greater specificity than tuberculin testing with an overall greater positive predictive value (relative to PMC) particularly in dairy herds. Comparison of the rates of recurrence of dairy herds cleared using this diagnostic test, to herds tested with tuberculin could resolve whether there is an increased risk of infection persistence. The use of defined antigens (Whelan et al., 2010), could reduce the impact of the biases in detection and open the door to the potential use of vaccination. However, validation of any new diagnostic test for bTB is challenging, given the intensity of testing required with the GB statutory system and the need for a high enough test specificity to even simply match the current system (Conlan et al., 2015).A.J.K. ConlanUniversity Lecturer in Epidemiology,AndJames L.N. WoodHead of Department of Veterinary Medicine andAlborada Professor of Equine and Farm Animal Science, Disease Dynamics Unit,Department of Veterinary Medicine,University of Cambridge,Cambridge, CB3 0ES, United KingdomE-mail address: ajkc2@cam.ac.uk (​mailto:ajkc2@cam.ac.uk​) ReferencesBrooks-Pollock, E., Conlan, A.J.K., Mitchell, A.P., Blackwell, R., McKinley, T.J., Wood, J.L.N., 2013. Age-dependent patterns of bovine tuberculosis in cattle. Vet. Res. 44, 97. doi:10.1186/1297-9716-44-97Brooks-Pollock, E., Wood, J.L.N., 2015. Eliminating bovine tuberculosis in cattle and badgers: insight from a dynamic model. Proc R Soc B 282, 20150374. doi:10.1098/rspb.2015.0374Conlan, A.J., McKinley, T.J., Karolemeas, K., Pollock, E.B., Goodchild, A.V., Mitchell, A.P., Birch, C.P., Clifton-Hadley, R.S., Wood, J.L., 2012. Estimating the hidden burden of bovine tuberculosis in Great Britain. PLoS Comput Biol 8, e1002730.Conlan, A.J., Pollock, E.B., McKinley, T.J., Mitchell, A.P., Jones, G.J., Vordermeier, M., Wood, J.L., 2015. Potential benefits of cattle vaccination as a supplementary control for bovine tuberculosis. PLoS Comput Biol 11, e1004038.Downs, S.H., Broughan, J.M., Goodchild, A.V., Upton, P.A., Durr, P.A., 2016. Responses to diagnostic tests for bovine tuberculosis in dairy and non-dairy cattle naturally exposed to Mycobacterium bovis in Great Britain. Vet. J. 216, 8–17. doi:10.1016/j.tvjl.2016.06.010Grant, W., 2009. Intractable Policy Failure: The Case of Bovine TB and Badgers. Br. J. Polit. Int. Relat. 11, 557–573. doi:10.1111/j.1467-856X.2009.00387.xKarolemeas, K., MKinley, T.J., Clifton-Hadley, R.S., Goodchild, A.V., Mitchell, A., Johnston, W.T., Conlan, A.J.K., Donnelly, C.A., Wood, J.L.N., 2010. Predicting prolonged bovine tuberculosis breakdowns in Great Britain as an aid to control. Prev. Vet. Med. 97, 183–190. doi:10.1016/j.prevetmed.2010.09.007Latest statistics on tuberculosis (TB) in cattle in Great Britain - Publications - GOV.UK [WWW Document], n.d. URL https://www.gov.uk/government/statistics/incidence-of-tuberculosis-tb-in-cattle-in-great-britain (accessed 7.25.16).Skuce, R.A., Allen, A.R., McDowell, S.W.J., 2012. Herd-Level Risk Factors for Bovine Tuberculosis: A Literature Review. Vet. Med. Int. 2012, e621210. doi:10.1155/2012/621210Whelan, A.O., Clifford, D., Upadhyay, B., Breadon, E.L., McNair, J., Hewinson, G.R., Vordermeier, M.H., 2010. Development of a Skin Test for Bovine Tuberculosis for Differentiating Infected from Vaccinated Animals. J. Clin. Microbiol. 48, 3176–3181. doi:10.1128/JCM.00420-10Brooks-Pollock, E., Wood, J.L.N., 2015. Eliminating bovine tuberculosis in cattle and badgers: insight from a dynamic model. Proc R Soc B 282, 20150374. doi:10.1098/rspb.2015.0374Conlan, A.J., McKinley, T.J., Karolemeas, K., Pollock, E.B., Goodchild, A.V., Mitchell, A.P., Birch, C.P., Clifton-Hadley, R.S., Wood, J.L., 2012. Estimating the hidden burden of bovine tuberculosis in Great Britain. PLoS Comput Biol 8, e1002730.Conlan, A.J., Pollock, E.B., McKinley, T.J., Mitchell, A.P., Jones, G.J., Vordermeier, M., Wood, J.L., 2015. Potential benefits of cattle vaccination as a supplementary control for bovine tuberculosis. PLoS Comput Biol 11, e1004038.Downs, S.H., Broughan, J.M., Goodchild, A.V., Upton, P.A., Durr, P.A., 2016. Responses to diagnostic tests for bovine tuberculosis in dairy and non-dairy cattle naturally exposed to Mycobacterium bovis in Great Britain. Vet. J. 216, 8–17. doi:10.1016/j.tvjl.2016.06.010Grant, W., 2009. Intractable Policy Failure: The Case of Bovine TB and Badgers. Br. J. Polit. Int. Relat. 11, 557–573. doi:10.1111/j.1467-856X.2009.00387.xKarolemeas, K., MKinley, T.J., Clifton-Hadley, R.S., Goodchild, A.V., Mitchell, A., Johnston, W.T., Conlan, A.J.K., Donnelly, C.A., Wood, J.L.N., 2010. Predicting prolonged bovine tuberculosis breakdowns in Great Britain as an aid to control. Prev. Vet. Med. 97, 183–190. doi:10.1016/j.prevetmed.2010.09.007Latest statistics on tuberculosis (TB) in cattle in Great Britain - Publications - GOV.UK [WWW Document], n.d. URL https://www.gov.uk/government/statistics/incidence-of-tuberculosis-tb-in-cattle-in-great-britain (accessed 7.25.16).Skuce, R.A., Allen, A.R., McDowell, S.W.J., 2012. Herd-Level Risk Factors for Bovine Tuberculosis: A Literature Review. Vet. Med. Int. 2012, e621210. doi:10.1155/2012/621210Whelan, A.O., Clifford, D., Upadhyay, B., Breadon, E.L., McNair, J., Hewinson, G.R., Vordermeier, M.H., 2010. Development of a Skin Test for Bovine Tuberculosis for Differentiating Infected from Vaccinated Animals. J. Clin. Microbiol. 48, 3176–3181. doi:10.1128/JCM.00420-10

Testing the dairy difference.

https://www.repository.cam.ac.uk/bitstream/handle/1810/290393/TVJL_Guest%20Editorialajkc2.doc?sequence=1&isAllowed=y

Testing the dairy difference.

Abstract

Similar works

Full text

Available Versions

Apollo (Cambridge)