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Farmland fragmentation is considered to be a defining feature of Northern Ireland’s (NI) agricultural landscape, influencing agricultural efficiency, productivity, and the spread of livestock diseases. Despite this, the full extent of farmland fragmentation in cattle farms in NI is not well understood, and little is known of how farmland fragmentation either influences, or is influenced by, different animal production types. Here, we describe and quantify farmland fragmentation in cattle farms for all of NI, using GIS processing of land parcel data to associate individual parcels with data on the cattle business associated with the land. We found that 35% of farms consisted of five or more fragments, with dairy farms associated with greater levels of farmland fragmentation, fragment dispersal and contact with contiguous neighbours compared to other production types. The elevated levels of farmland fragmentation in dairy production compared to non-dairy, may be associated with the recent expansion of dairy farms by land acquisition, following the abolition of the milk quota system in 2015. The comparatively high levels of farmland fragmentation observed in NI cattle farms may also have important implications for agricultural productivity and epidemiology alike. Whilst highly connected pastures could facilitate the dissemination of disease, highly fragmented land could also hamper productivity via diseconomies of scale, such as preventing the increase of herd sizes or additionally, adding to farm costs by increasing the complexity of herd management.

Background Despite rigorous controls placed on herds which disclose ante-mortem test positive cattle to bovine tuberculosis, caused by the infection of Mycobacterium bovis, many herds in Northern Ireland (NI) experience prolonged breakdowns. These herds represent a considerable administrative and financial burden to the State and farming community. Methods A retrospective observational study was conducted to better understand the factors associated with breakdown duration, which was modelled using both negative binomial and ordinal regression approaches. Results Six explanatory variables were important predictors of breakdown length in both models; herd size, the number of reactors testing positive in the initial SICCT test, the presence of a lesioned animal at routine slaughter (LRS), the count of M. bovis genotypes during the breakdown (MLVA richness), the local herd-level bTB prevalence, and the presence of herds linked via management factors (associated herds). We report that between 2008 and 2014, mean breakdown duration in NI was 226 days (approx. seven months; median: 188 days). In the same period, however, more than 6% of herds in the region remained under movement restriction for more than 420 days (13 months); almost twice as long as the mean. The MLVA richness variable was a particularly important predictor of breakdown duration. We contend that this variable primarily represents a proxy for beef fattening herds, which can operate by purchasing cattle and selling animals straight to slaughter, despite prolonged trading restrictions. For other herd types, the model supports the hypothesis that prolonged breakdowns are a function of both residual infection within the herd, and infection from the environment (e.g. infected wildlife, contiguous herds and/or a contaminated environment). The impact of badger density on breakdown duration was assessed by including data on main sett (burrow) density. Whilst a positive association was observed in the univariate analysis, confounding with other variables means that the contribution of badgers to prolonged breakdowns was not clear from our study. We do not fully reject the hypothesis that badgers are implicated in prolonging bTB breakdowns via spillback infection, but given our results, we posit that increased disease risk from badgers is unlikely to simply be a function of increasing badger density measured using sett metrics.

Bovine tuberculosis remains a challenging endemic pathogen of cattle in many parts of the globe. Spatial clustering of Mycoacterium bovis molecular types in cattle suggests that local factors are the primary drivers of spread. Northern Ireland’s agricultural landscape is comprised of highly fragmented farms, distributed across spatially discontinuous land parcels, and these highly fragmented farms are thought to facilitate localised spread. We conducted a matched case control study to quantify the risks of bovine tuberculosis breakdown with farm area, farm fragmentation, fragment dispersal, and contact with neighbouring herds. Whilst our results show small but significant increases in breakdown risk associated with each factor, these relationships were strongly confounded with the number of contiguous neighbours with bovine tuberculosis. Our key finding was that every infected neighbour led to an increase in the odds of breakdown by 40% to 50%, and that highly fragmented farms were almost twice as likely to have a bTB positive neighbour compared to nonfragmented farms. Our results suggest that after controlling for herd size, herd type, spatial and temporal factors, farm fragmentation increasingly exposes herds to infection originating from first-order spatial neighbours. Given Northern Ireland’s particularly fragmented landscape, and reliance on short-term leases, our data support the hypothesis that between-herd contiguous spread is a particularly important component of the region’s bovine tuberculosis disease system.

Abstract Background Bovine tuberculosis (bTB), caused by Mycobacterium bovis, remains a significant problem for livestock industries in many countries worldwide including Northern Ireland, where a test and slaughter regime has utilised the Single Intradermal Comparative Cervical Tuberculin (SICCT) test since 1959. We investigated the variation in post-mortem confirmation based on bTB visible lesion (VL) presence during herd breakdowns using two model suites. We investigated animal-level characteristics, while controlling for herd-level factors and clustering. We were interested in potential impacts of concurrent infection, and therefore we assessed whether animals with evidence of liver fluke infection (Fasciola hepatica; post-mortem inspection), M. avium reactors (animals with negative M. bovis-avium (b-a) tuberculin reactions) or Bovine Viral Diarrhoea Virus (BVDV; RT-PCR tested) were associated with bTB confirmation. Results The dataset included 6242 animals removed during the 14 month study period (2013–2015). bTB-VL presence was significantly increased in animals with greater b-a reaction size at the disclosing SICCT test (e.g. b-a = 5-9 mm vs. b-a = 0 mm, adjusted Odds ratio (aOR): 14.57; p 0.1). Conclusions Our results suggest that neither co-infection of liver fluke nor BVDV had a significant effect on the presence of VLs in this high-risk cohort. M. avium tuberculin reactors had a significantly increased risk of disclosing with a bTB lesion, which could be related to the impact of co-infection with M. avium subsp. paratuberculosis (MAP) affecting the performance of the SICCT however further research in this area is required. Movements, test history, breed and age were important factors influencing confirmation in high-risk animals.

Background: Bovine tuberculosis (bTB; Mycobacterium bovis) remains a significant problem in a number of countries, and is often found where M. avium subsp. paratuberculosis (MAP) is also present. In the United Kingdom, bTB has been difficult to eradicate despite long-term efforts. Co-infection has been proposed as one partial mechanism thwarting eradication.Methods: A retrospective case-control study of 4,500 cattle herds in Northern Ireland, where serological testing of cattle for MAP, was undertaken (2004–2015). Blood samples were ELISA tested for MAP; infection of M. bovis was identified in herds by the comparative tuberculin test (CTT) and through post-mortem evidence of infection. Case-herds were those experiencing a confirmed bTB breakdown; control-herds were not experiencing a breakdown episode at the time of MAP testing. A second model included additional testing data of feces samples (culture and PCR results) to better inform herd MAP status. Multi-level hierarchical models were developed, controlling for selected confounders. A sensitivity analysis of the effect of MAP sample numbers per event and the prior timing of tuberculin-testing was undertaken.Results: 45.2% (n = 250) of case observations and 36.0% (3,480) of control observations were positive to MAP by ELISA (45.8% and 36.4% when including ancillary fecal testing, respectively). Controlling for known confounders, the adjusted odds ratio (aOR) for this association was 1.339 (95%CI:1.085–1.652; including ancillary data aOR:1.356;95%CI:1.099–1.673). The size-effect of the association increased with the increasing number of samples per event used to assign herd MAP status (aOR:1.883 at >2 samples, to aOR:3.863 at >10 samples), however the estimated CI increased as N decreased. 41.7% of observations from chronic herds were MAP serology-positive and 32.2% from bTB free herds were MAP positive (aOR: 1.170; 95%ci: 0.481–2.849).Discussion: Cattle herds experiencing a bTB breakdown were associated with increased risk of having a positive MAP status. Chronic herds tended to exhibit higher risk of a positive MAP status than bTB free herds, however there was less support for this association when controlling for repeated measures and confounding. MAP co-infection may be playing a role in the success of bTB eradiation schemes, however further studies are required to understand the mechanisms and to definitively establish causation.

Bovine tuberculosis surveillance in Northern Ireland includes Multiple-Locus Variable number tandem repeat Analysis (MLVA) to determine the Mycobacterium bovis genetic type present in both cattle and the predominant wildlife host, the European badger (Meles meles). These data are useful for investigating clusters of infection and understanding the scale at which interspecific transmission may occur. We utilised a comprehensive dataset of routinely sampled isolates from infected cattle and from badgers killed in road-traffic accidents to investigate the spatial co-location of MLVA types in, and between, the badger and cattle populations. Furthermore, we investigated the hypothesis that the type of farming enterprise might explain some variation in this relationship. MLVA types were spatially co-localised in cattle and road-traffic accident (RTA) badger hosts, indicative of a shared epidemic. Dairy herds were more likely to have at least one MLVA type in common with nearby RTA badgers, compared to non-dairy herd types. Marginally more MLVA spatial clustering was observed in non-dairy herds, which may be a consequence of relatively more between-herd movements. For the cattle population, local transmission mechanisms such as infection from contiguous herds, infectious wildlife and short-range between-herd cattle movements appear primarily to drive the epidemic: there appears to be a more limited role for long-range movements. Animal management practices are likely to be the driving force behind this observation, as beef rearing is associated with elevated numbers of animal movements compared to dairy herds.