In the Republic of Ireland, the herd-level incidence of bovine tuberculosis (bTB), caused by Mycobacterium bovis, reached 6.40

Mycobacterium bovis the main agent of bovine tuberculosis (bTB), presents as a series of spatially-localised micro-epidemics across landscapes. Classical molecular typing methods applied to these micro-epidemics, based on genotyping a few variable loci, have significantly improved our understanding of potential epidemiological links between outbreaks. However, they have limited utility owing to low resolution. Conversely, whole-genome sequencing (WGS) provides the highest resolution data available for molecular epidemiology, producing richer outbreak tracing, insights into phylogeography and epidemic evolutionary history. We illustrate these advantages by focusing on a common single lineage of M. bovis (1.140) from Northern Ireland. Specifically, we investigate the spatial sub-structure of 20 years of herd-level multi locus VNTR analysis (MLVA) surveillance data and WGS data from a down sampled subset of isolates of this MLVA type over the same time frame. We mapped 2108 isolate locations of MLVA type 1.140 over the years 2000–2022. We also mapped the locations of 148 contemporary WGS isolates from this lineage, over a similar geographic range, stratifying by single nucleotide polymorphism (SNP) relatedness cut-offs of 15 SNPs. We determined a putative core range for the 1.140 MLVA type and SNP-defined sequence clusters using a 50 % kernel density estimate, using cattle movement data to inform on likely sources of WGS isolates found outside of core ranges. Finally, we applied Bayesian phylogenetic methods to investigate past population history and reproductive number of the 1.140 M . bovis lineage. We demonstrate that WGS SNP-defined clusters exhibit smaller core ranges than the established MLVA type - facilitating superior disease tracing. We also demonstrate the superior functionality of WGS data in determining how this lineage was disseminated across the landscape, likely via cattle movement and to infer how its effective population size and reproductive number has been in flux since its emergence. These initial findings highlight the potential of WGS data for routine monitoring of bTB outbreaks.

Bovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Lack of understanding of transmission dynamics may undermine eradication efforts. Pathogen whole-genome sequencing improves epidemiological inferences, providing a means to determine the relative importance of inter- and intra-species host transmission for disease persistence. We sequenced an exceptional data set of 619 Mycobacterium bovis isolates from badgers and cattle in a 100 km2 bTB ‘hotspot’ in Northern Ireland. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided a unique opportunity to study disease transmission dynamics in unparalleled detail. Additionally, to assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area. Birth death models and TransPhylo analyses indicated that cattle were likely driving the local epidemic, with transmission from cattle to badgers being more common than badger to cattle. Furthermore, the presence of significant badger population genetic structure in the landscape was not associated with the spatial distribution of M. bovis genetic diversity, suggesting that badger-to-badger transmission is not playing a major role in transmission dynamics. Our data were consistent with badgers playing a smaller role in transmission of M. bovis infection in this study site, compared to cattle. We hypothesize, however, that this minor role may still be important for persistence. Comparison to other areas suggests that M. bovis transmission dynamics are likely to be context dependent, with the role of wildlife being difficult to generalize.

Abstract Culling the main wildlife host of bovine tuberculosis in Great Britain (GB) and Ireland, the European badger (Meles meles), has been employed in both territories to reduce infections in cattle. In GB, this has been controversial, with results suggesting that culling induces disturbance to badger social structure, facilitating wider disease dissemination. Previous analyses hypothesized that even very low‐level, selective culling may cause similar deleterious effects by increasing ranging of individuals and greater mixing between social groups. To assess this hypothesis, a novel, prospective, landscape‐scale ‘before‐and‐after’ Test and Vaccinate or Remove (TVR) study was implemented. Test‐positive badgers were culled and test‐negative badgers were Bacillus Calmette–Guérin (BCG) vaccinated and released. Mark–recapture metrics of badger ranging and genetic metrics of social group relatedness did not change significantly over the study period. However, selective culling was associated with a localized reduction in social group relatedness in culled groups. Ecological context is important; extrapolation across territories and other disease epidemiological systems (epi‐systems) is likely to be challenging. However, we demonstrate that small‐scale, selective removal of test‐positive badgers was not associated with metrics of increased ranging but was associated with localized changes in social group relatedness. This adds to the evidence base on badger control options for policy makers.

Understanding how an emergent pathogen successfully establishes itself and persists in a previously unaffected population is a crucial problem in disease ecology. In multi-host pathogen systems this problem is particularly difficult, as the importance of each host species to transmission is often poorly characterised, and the epidemiology of the disease is complex. Opportunities to observe and analyse such emergent scenarios are few. Here, we exploit a unique dataset combining densely-collected data on the epidemiological and evolutionary characteristics of an outbreak of Mycobacterium bovis ( M. bovis, the causative agent of bovine tuberculosis, bTB) in a population of cattle and badgers in an area considered low-risk for bTB, that has no previous record of either persistent infection in cattle, or of any infection in wildlife. We analyse the outbreak dynamics using a combination of mathematical modelling, machine learning and Bayesian evolutionary analyses. Comparison to M. bovis whole-genome sequences from Northern Ireland confirmed this to be a single introduction of the pathogen from the latter region, with evolutionary analysis supporting an introduction directly into the local cattle population at least six years prior to its first discovery in badgers. Once introduced, the evidence supports M. bovis epidemiological dynamics passing through two phases, the first dominated by cattle-to-cattle transmission before becoming established in the local badger population. These findings emphasise the importance of disease surveillance for early containment of outbreaks, in particular for pathogens not causing immediately evident symptoms in the infected host, and highlight the utility of combining dynamic modelling and phylogenetic analyses for understanding the often complex infection dynamics associated with emergent outbreaks.

Abstract BackgroundJohne’s disease is a chronic granulomatous enteritis of cattle and other ruminants of economic, animal and public health significance, caused by Mycobacterium avium subsp. paratuberculosis. It is endemic in UK, but there is currently limited information in Northern Ireland. To address this gap, for the first time surveillance data were used to estimate seroprevalence and explore risk factors for a cohort of herds that participate in a voluntary scheme. MethodsA Bayesian approach, Gibbs sampling was used to estimate animal-level true prevalence. The effects of test sensitivity, specificity, and true prevalence and number of animals tested and critical number of positive reactors were considered for herd test sensitivity, specificity and true prevalence estimation. Logistic regression was used to develop a model associating herd status with putative risk factors.Results46,715 cattle in 431 dairy herds were tested by ELISA between 2010 and 2019. 2138 (4.6%) animals were positive. At least one ELISA-positive case was detected in 239 herds (55.4%, 95%CI: 50.7 - 60.1) whereas, 152 herds recorded ≥2 ELISA-positives (35.2 %, 95% CI: 30.7 - 39.8). The mean true herd prevalence was estimated to be 34.7% and 43.9 % for k ≥1 and k ≥2 critical number of reactor herds respectively. The study estimated 9.5 % (95%PPI: 0.5 - 21.4), 32.8 % (95 % PPI: 17.1 - 50.8) and 98.3 % (95 % PPI: 95.6 - 99.9), median values for animal-level true prevalence, test sensitivity and specificity respectively.Herds sized ≥ 100 were between 1.8 and 5.5(95%CI: of the OR) times more likely to test MAP ELISA-positive than herds with < 100 cattle. Herds with mean animal age of ≥5 years were between 1.5 and 3.6 (95% CI: of the OR) times more likely to have MAP ELISA-positive results than herds with a mean animal age of < 5 years. ConclusionResults of this study estimated disease prevalence and identified some associated risk factors which improves understanding of the local epidemiology, and indicate the need for establishing a sustainable control programme. Further investigation is required to better understand local epidemiology and associated production and economic losses.

We describe application of whole genome sequencing (WGS) to a collection of 197 Mycobacterium avium subsp paratuberculosis (MAP) isolates gathered from 122 cattle herds across 27 counties of the island of Ireland. We compare WGS to MAP diversity quantified using mycobacterial interspersed random unit - variable number tandem repeats (MIRU-VNTR). While MIRU-VNTR showed only two major types, WGS could split the 197 isolates into eight major groups. We also found six isolates corresponding to INMV 13, a novel MIRU-VNTR type for Ireland. Evidence for dispersal of MAP across Ireland via cattle movement could be discerned from the data, with mixed infections present in several herds. Furthermore, comparisons of MAP WGS data from Ireland to data from Great Britain and continental Europe revealed many instances of close genetic similarity and hence evidence for international transmission of infection. BEAST MASCOT structured coalescent analyses, with relaxed and strict molecular clocks, estimated the substitution rate to be 0.10-0.13 SNPs/site/year and disclosed greater transitions per lineage per year from Europe to Ireland, indicating transmission into Ireland. Our work therefore reveals new insight into the seeding of MAP infection across Ireland, highlighting how WGS can inform policy formulation to ultimately control MAP transmission at local, national and international scales.

Bovine tuberculosis (bTB) is one of the globe’s most common, multihost zoonoses and results in substantial socioeconomic costs for governments, farming industries, and tax payers. Despite decades of surveillance and research, surprisingly, little is known about the exact mechanisms of transmission. In particular, as a facultative intracellular pathogen, to what extent does survival of the causative agent, Mycobacterium tuberculosis var. bovis (M. bovis), in the environment constitute an epidemiological risk for livestock and wildlife? Due largely to the classical pathology of cattle cases, the received wisdom was that bTB was spread by direct inhalation and exchange of bioaerosols containing droplets laden with bacteria. Other members of the Mycobacterium tuberculosis complex (MTBC) exhibit differing host ranges, an apparent capacity to persist in environmental fomites, and they favour a range of different transmission routes. It is possible, therefore, that infection from environmental sources of M. bovis could be a disease transmission risk. Recent evidence from GPS-collared cattle and badgers in Britain and Ireland suggests that direct transmission by infectious droplets or aerosols may not be the main mechanism for interspecies transmission, raising the possibility of indirect transmission involving a contaminated, shared environment. The possibility that classical pulmonary TB can be simulated and recapitulated in laboratory animal models by ingestion of contaminated feed is a further intriguing indication of potential environmental risk. Livestock and wildlife are known to shed M. bovis onto pasture, soil, feedstuffs, water, and other fomites; field and laboratory studies have indicated that persistence is possible, but variable, under differing environmental conditions. Given the potential infection risk, it is timely to review the available evidence, experimental approaches, and methodologies that could be deployed to address this potential blind spot and control point. Although we focus on evidence from Western Europe, the concepts are widely applicable to other multihost bTB episystems.

AbstractBackgroundBovine tuberculosis (bTB) is a costly, epidemiologically complex, multi-host, endemic disease. Pathogen whole genome sequencing can improve the resolution of epidemiological tracing. We genome sequenced an exceptional data set of 619Mycobacterium bovisisolates from badgers and cattle in a 100km2bTB ‘hotspot’. Historical molecular subtyping data permitted the targeting of an endemic pathogen lineage, whose long-term persistence provided an opportunity to study genome epidemiology in detail. To assess whether badger population genetic structure was associated with the spatial distribution of pathogen genetic diversity, we microsatellite genotyped hair samples from 769 badgers trapped in this area.ResultsEight lineages ofM. boviswere circulating in the study area, seven of which were likely non-endemic, and imported by animal movement. The endemic lineage exhibited low genetic diversity with an average inter-isolate genetic distance of 7.6 SNPs (s.d. ± 4.0), consistent with contemporary transmission. Bayesian phylogenetic methods determined an evolutionary rate of 0.30 substitutions per genome per year for this lineage, estimating its emergence 40-50 years before present, while Bayesian Skyline analysis identified significant population expansion of the endemic lineage in the 1990s and again in 2011-2012. The phylogeny revealed distinct sub-lineages, all of which contained isolates from both cattle and badger hosts, indicative of the sharing of closely related strains and inter-species transmission. However, the presence of significant badger population genetic structure was not associated with the spatial distribution ofM. bovisgenetic diversity.ConclusionsOur data provided unparalleled detail on the evolutionary history of an endemicM. bovislineage. Findings are consistent with ongoing interspecies transmission in the study area but suggest that badger intra-species transmission may not be a major driver of persistence in this area. In addition, the data collected permitted the tracking of incursions of novel pathogen lineages into the study area and means to determine if they were involved in disease transmission.

The addition of cattle health and immunity traits to genomic selection indices holds promise to increase individual animal longevity and productivity, and decrease economic losses from disease. However, highly variable genomic loci that contain multiple immune-related genes were poorly assembled in the first iterations of the cattle reference genome assembly and underrepresented during the development of most commercial genotyping platforms. As a consequence, there is a paucity of genetic markers within these loci that may track haplotypes related to disease susceptibility. By using hierarchical assembly of bacterial artificial chromosome inserts spanning 3 of these immune-related gene regions, we were able to assemble multiple full-length haplotypes of the major histocompatibility complex, the leukocyte receptor complex, and the natural killer cell complex. Using these new assemblies and the recently released ARS-UCD1.2 reference, we aligned whole-genome shotgun reads from 125 sequenced Holstein bulls to discover candidate variants for genetic marker development. We selected 124 SNPs, using heuristic and statistical models to develop a custom genotyping panel. In a proof-of-principle study, we used this custom panel to genotype 1,797 Holstein cows exposed to bovine tuberculosis (bTB) that were the subject of a previous GWAS study using the Illumina BovineHD array. Although we did not identify any significant association of bTB phenotypes with these new genetic markers, 2 markers exhibited substantial effects on bTB phenotypic prediction. The models and parameters trained in this study serve as a guide for future marker discovery surveys particularly in previously unassembled regions of the cattle genome.

Multi-host pathogens are particularly difficult to control, especially when at least one of the hosts acts as a hidden reservoir. Deep sequencing of densely sampled pathogens has the potential to transform this understanding, but requires analytical approaches that jointly consider epidemiological and genetic data to best address this problem. While there has been considerable success in analyses of single species systems, the hidden reservoir problem is relatively under-studied. A well-known exemplar of this problem is bovine Tuberculosis, a disease found in British and Irish cattle caused by Mycobacterium bovis, where the Eurasian badger has long been believed to act as a reservoir but remains of poorly quantified importance except in very specific locations. As a result, the effort that should be directed at controlling disease in badgers is unclear. Here, we analyse densely collected epidemiological and genetic data from a cattle population but do not explicitly consider any data from badgers. We use a simulation modelling approach to show that, in our system, a model that exploits available cattle demographic and herd-to-herd movement data, but only considers the ability of a hidden reservoir to generate pathogen diversity, can be used to choose between different epidemiological scenarios. In our analysis, a model where the reservoir does not generate any diversity but contributes to new infections at a local farm scale are significantly preferred over models which generate diversity and/or spread disease at broader spatial scales. While we cannot directly attribute the role of the reservoir to badgers based on this analysis alone, the result supports the hypothesis that under current cattle control regimes, infected cattle alone cannot sustain M. bovis circulation. Given the observed close phylogenetic relationship for the bacteria taken from cattle and badgers sampled near to each other, the most parsimonious hypothesis is that the reservoir is the infected badger population. More broadly, our approach demonstrates that carefully constructed bespoke models can exploit the combination of genetic and epidemiological data to overcome issues of extreme data bias, and uncover important general characteristics of transmission in multi-host pathogen systems.

The colonization of Ireland by mammals has been the subject of extensive study using genetic methods and forms a central problem in understanding the phylogeography of European mammals after the Last Glacial Maximum. Ireland exhibits a depauperate mammal fauna relative to Great Britain and continental Europe, and a range of natural and anthropogenic processes have given rise to its modern fauna. Previous Europe-wide surveys of the European badger (Meles meles) have found conflicting microsatellite and mitochondrial DNA evidence in Irish populations, suggesting Irish badgers have arisen from admixture between human imported British and Scandinavian animals. The extent and history of contact between British and Irish badger populations remains unclear. We use comprehensive genetic data from Great Britain and Ireland to demonstrate that badgers in Ireland's northeastern and southeastern counties are genetically similar to contemporary British populations. Simulation analyses suggest this admixed population arose in Ireland 600–700 (CI 100–2600) years before present most likely through introduction of British badgers by people. These findings add to our knowledge of the complex colonization history of Ireland by mammals and the central role of humans in facilitating it.

Background.Despite rigorous controls placed on herds which disclose antemortem 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.

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.

Background: In the recent past (1997-2012), Northern Ireland in the United Kingdom suffered an outbreak of Brucella abortus, which at its height affected over 200 cattle herds. Initially, isolates were characterized using multi-locus variable number tandem repeats analysis (MLVA). While informative in this setting, hyper-variability in some loci limited the resolution necessary to infer fine-scale disease transmission networks. Consequently, we applied whole-genome sequencing to isolates from this outbreak to evaluate higher resolution markers for disease epizootiology. Results: Phylogenetic analysis revealed that the B. abortus outbreak in Northern Ireland was caused by two distinct pathogen lineages. One contained isolates consistent with the 1997-2012 outbreak being linked to a previous endemic infection thought eradicated. The dominant second lineage exhibited little genetic diversity throughout the recrudescent outbreak, with limited population sub-structure evident. This finding was inconsistent with prior MLVA molecular characterizations that suggested the presence of seven clonal complexes. Spatio-temporal modeling revealed a significant association of pairwise SNP differences between isolates and geographic distances. However, effect sizes were very small due to reduced pathogen diversity. Conclusions: Genome sequence data suggested that hyper-variability in some MLVA loci contributed to an overestimate of pathogen diversity in the most recent outbreak. The low diversity observed in our genomic dataset made it inappropriate to apply phylodynamic methods to these data. We conclude that maintaining data repositories of genome sequence data will be invaluable for source attribution/epizootiological inference should recrudescence ever re-occur. However genomic epizootiological methods may have limited utility in some settings, such as when applied to recrudescent/re-emergent infections of slowly-evolving bacterial pathogens.

Bovine tuberculosis surveillance in Northern Ireland includes Multiple-Locus Variable number tandem repeat Analysis (MLVA) to determine theMycobacterium bovisgenetic 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.

Investigating genetically-structured diversity in pathogen populations over time is important to better understand disease maintenance and spread. Herd-level surveillance of Mycobacterium bovis genotypes (multi-locus VNTR analysis types, MLVA types) from all culture-confirmed bovine tuberculosis (TB) herd cases was undertaken in Northern Ireland (NI), generating an unparalleled, longitudinal, population-level 14-year survey for this pathogen. Across this population, 295 genetically-distinct M. bovis MLVA types were identified in the 19,717 M. bovis isolates surveyed. Of these, the most frequent was MLVA type 002 (23.0%); 151 MLVA types were represented more than once, in groups ranging from 2 to 4438 isolates. Only 23 MLVA types were isolated in all 14 years. Investigating inter-annual frequency of M. bovis MLVA types, examples of statistically-significant expansions (MLVA types 002, 004, 006, 009 and 027), contractions (MLVA types 001, 007 and 011) and maintenance (MLVA types 003 and 005) were disclosed, during a period of fluctuating bovine TB herd-level incidence at the NI scale. The fixed period frequency distribution of MLVA types remained highly right-skewed. Novel VNTR copy number variant MLVA types (N= 242; an average of 17 per annum) were identified throughout the survey. The MLVA type distribution in the landscape was not random; MLVA types showed statistically-significant geographical localization and strong spatial associations with Divisional Veterinary Office (DVO) regions. There was also evidence of differential risk of particular MLVA types across breeds (Holstein/Friesian vs. other), age-class, and sex and some evidence of an association between the number of animals testing positive for bovine TB during the disclosing test and particular MLVA types, although there was substantial variation.

Background We used genetic Multi-Locus VNTR Analysis (MLVA) data gathered from surveillance efforts to better understand the ongoing bovine tuberculosis (bTB) epidemic in Northern Irish cattle herds. We modelled the factors associated with Mycobacterium bovis MLVA genotype richness at three analytical scales; breakdown level, herd level, and patch level, and compared the results between dairy and non-dairy production types. Results In 83% of breakdowns and in 63% of herds, a single MLVA genotype was isolated. Five or more MLVA genotypes were found in less than 3 % of herds. Herd size and the total number of reactors were important explanatory variables, suggesting that increasing MLVA genotype richness was positively related to increases in the number of host animals. Despite their smaller relative size, however, the highest MLVA genotype richness values were observed in non-dairy herds. Increasing inwards cattle movements were important positive predictors of MLVA genotype richness, but mainly in non-dairy settings. Conclusions The principal finding is that low MLVA genotype richness indicates that small-scale epidemics, e.g. wildlife, contiguous farms, and within-herd recrudescence, are important routes of M. bovis infection in cattle herds. We hypothesise that these mechanisms will maintain, but may not explicitly increase, MLVA genotype richness. The presence of elevated MLVA richness is relatively rare and likely indicates beef fattening enterprises, which purchase cattle from over long distances. Cattle movements were furthermore an important predictor of MLVA genotype richness in non-dairy herds, but not in dairy herds; this may represent reduced cattle purchasing levels in dairy enterprises, compared to beef. These observations allude to the relative contribution of different routes of bTB infection between production types; we posit that infection associated with local factors may be more evident in dairy herds than beef herds, however in beef herds, inwards movements offer additional opportunities for introducing M. bovis into the herd.