Post-mortem surveillance of bovine tuberculosis in Ireland: herd-level variation in the probability of herds disclosed with lesions at routine slaughter to have skin test reactors at follow-up test

Abstract

Post-mortem surveillance in Ireland discloses skin-test negative cattle with presumptive evidence of infection of Mycobacterium bovis (lesions at routine slaughter (LRS)), the causative agent of bovine tuberculosis (bTB). Laboratory confirmation of lesions has impacts on trade restrictions for herds, therefore if laboratory capacity was diminished, how herds are treated would require an informed risk policy. Here we report the proportion of herds with subsequent evidence of within-herd transmission, based on skin-test results. We assess how herd-size, herd-type, and bTB-history affect the probability of additional reactors at follow-up test using univariable and multivariable random-effects models. The study represents a rapid response to developing an evidential base for policy demands during an extraordinary event, the COVID-19 epidemic in Ireland. A dataset from 2005 to 2019 of breakdowns were collated. Overall, 20,116 breakdowns were initiated by LRS cases. During the index tests of these breakdowns, 3931 revealed ≥1 skin-test reactor animals (19.54%; ≥1 standard reactors: 3827; 19.02%). Increasing herd-size was associated with reactor disclosure on follow-up. For small herds (<33 animals), 11.74% of follow-up tests disclosed ≥1 reactor; 24.63% of follow-up tests from very large herds (>137) disclosed ≥1 reactors. Beef (13.87%) and "other" (13%) herd production types had lower proportion of index tests with reactors in comparison with dairy (28.27%) or suckler (20.48%) herds. Historic breakdown size during the previous 3-years was associated reactor disclosure risk on follow-up. Our results are useful for rapid tailored policy development aimed at identifying higher risk herds.

Keywords: Bovine tuberculosis; Disease control; Evidence-based policy; Veterinary epidemiology.

Fig. 1

Relationship between reactor disclosure risk on follow-up and year. Point estimates are from a logistic model with one predictor, year, modelled as a categorical variable. Trend line is from a linear model using year as a continuous variable. Error bars = 95%CI

Fig. 2

Variation of marginal risk of additional disclosure of skin test positive animals after lesions found at routine slaughter in relation to herd size and herd enterprise type