Identifying genotype specific elevated-risk areas and associated herd risk factors for bovine tuberculosis spread in British cattle

Bovine tuberculosis in Taiwan, 2008-2019

Bovine tuberculosis (bTB) is a zoonosis caused by Mycobacterium bovis. The impact of bTB on global TB control has been underestimated. We adopted the One Health approach to human bTB surveillance in Taiwan. Of 20,972 human TB cases, 202 (1.0%) were bTB, 78.2% were in males, 85.1% were new cases, 83.2% were pulmonary TB, and most were in Central (52.5%) and Southern (24.8%) Taiwan. Only 18.8% of bTB patients had known animal contact. Of the 202 human M. bovis strains, 100% were resistant to pyrazinamide (PZA), 30.2% were concurrently resistant to isoniazid (INH) and 2.0% were multidrug resistant, defined as being resistant to at least INH and rifampin. Whereas, of the 22 animal M. bovis strains, 100% and 22.7% were resistant to PZA and INH, respectively. Seven spoligotypes and 25 mycobacterial interspersed repetitive unit genotypes were identified. The predominant genotype, SB0265, was also prevalent in livestock. Notably, six animal-specific M. bovis genotypes were identified. bTB differential diagnosis and drug resistance detection are crucial for TB control. Comprehensive surveillance and human-animal interface investigations are needed.

Tuberculosis in badgers where the bovine tuberculosis epidemic is expanding in cattle in England

Bovine tuberculosis (bTB) is an important animal health and economic problem for the cattle industry and a potential zoonotic threat. Wild badgers (Meles meles) play a role on its epidemiology in some areas of high prevalence in cattle, particularly in the UK and Republic of Ireland and increasingly in parts of mainland Europe. However, little is known about the involvement of badgers in areas on the spatial edge of the cattle epidemic, where increasing prevalence in cattle is seen. Here we report the findings of a study of found-dead (mainly road-killed) badgers in six counties on the edge of the English epidemic of bTB in cattle. The overall prevalence of Mycobacterium tuberculosis complex (MTC) infection detected in the study area was 51/610 (8.3%, 95% CI 6.4-11%) with the county-level prevalence ranging from 15 to 4-5%. The MTC spoligotypes of recovered from badgers and cattle varied: in the northern part of the study area spoligotype SB0129 predominated in both cattle and badgers, but elsewhere there was a much wider range of spoligotypes found in badgers than in cattle, in which infection was mostly with the regional cattle spoligotype. The low prevalence of MTC in badgers in much of the study area, and, relative to in cattle, the lower density of sampling, make firm conclusions difficult to draw. However, with the exception of Cheshire (north-west of the study area), little evidence was found to link the expansion of the bTB epidemic in cattle in England to widespread badger infection.

Tooling-up for infectious disease transmission modelling

In this introduction to the Special Issue on methods for modelling of infectious disease epidemiology we provide a commentary and overview of the field. We suggest that the field has been through three revolutions that have focussed on specific methodological developments; disease dynamics and heterogeneity, advanced computing and inference, and complexity and application to the real-world. Infectious disease dynamics and heterogeneity dominated until the 1980s where the use of analytical models illustrated fundamental concepts such as herd immunity. The second revolution embraced the integration of data with models and the increased use of computing. From the turn of the century an emergence of novel datasets enabled improved modelling of real-world complexity. The emergence of more complex data that reflect the real-world heterogeneities in transmission resulted in the development of improved inference methods such as particle filtering. Each of these three revolutions have always kept the understanding of infectious disease spread as its motivation but have been developed through the use of new techniques, tools and the availability of data. We conclude by providing a commentary on what the next revoluition in infectious disease modelling may be.

Effects of trading networks on the risk of bovine tuberculosis incidents on cattle farms in Great Britain

Trading animals between farms and via markets can provide a conduit for spread of infections. By studying trading networks, we might better understand the dynamics of livestock diseases. We constructed ingoing contact chains of cattle farms in Great Britain that were linked by trading, to elucidate potential pathways for the transmission of infection and to evaluate their effect on the risk of a farm experiencing a bovine tuberculosis (bTB) incident. Our findings are consistent with variation in bTB risk associated with region, herd size, disease risk area and history of previous bTB incidents on the root farm and nearby farms. However, we also identified effects of both direct and indirect trading patterns, such that connections to more farms in the England High-Risk Area up to three movements away from the root farm increased the odds of a bTB incident, while connections with more farms in the England Low-Risk Area up to eight movements away decreased the odds. Relative to other risk factors for bTB, trading behaviours are arguably more amenable to change, and consideration of risks associated with indirect trading, as well direct trading, might therefore offer an additional approach to bTB control in Great Britain.

The Many Hosts of Mycobacteria 8 (MHM8): A conference report

Mycobacteria are important causes of disease in human and animal hosts. Diseases caused by mycobacteria include leprosy, tuberculosis (TB), nontuberculous mycobacteria (NTM) infections and Buruli Ulcer. To better understand and treat mycobacterial disease, clinicians, veterinarians and scientists use a range of discipline-specific approaches to conduct basic and applied research, including conducting epidemiological surveys, patient studies, wildlife sampling, animal models, genetic studies and computational simulations. To foster the exchange of knowledge and collaboration across disciplines, the Many Hosts of Mycobacteria (MHM) conference series brings together clinical, veterinary and basic scientists who are dedicated to advancing mycobacterial disease research. Started in 2007, the MHM series recently held its 8th conference at the Albert Einstein College of Medicine (Bronx, NY). Here, we review the diseases discussed at MHM8 and summarize the presentations on research advances in leprosy, NTM and Buruli Ulcer, human and animal TB, mycobacterial disease comorbidities, mycobacterial genetics and 'omics, and animal models. A mouse models workshop, which was held immediately after MHM8, is also summarized. In addition to being a resource for those who were unable to attend MHM8, we anticipate this review will provide a benchmark to gauge the progress of future research concerning mycobacteria and their many hosts.

Combining genomics and epidemiology to analyse bi-directional transmission of Mycobacterium bovis in a multi-host system

Quantifying pathogen transmission in multi-host systems is difficult, as exemplified in bovine tuberculosis (bTB) systems, but is crucial for control. The agent of bTB, Mycobacterium bovis, persists in cattle populations worldwide, often where potential wildlife reservoirs exist. However, the relative contribution of different host species to bTB persistence is generally unknown. In Britain, the role of badgers in infection persistence in cattle is highly contentious, despite decades of research and control efforts. We applied Bayesian phylogenetic and machine-learning approaches to bacterial genome data to quantify the roles of badgers and cattle in M. bovis infection dynamics in the presence of data biases. Our results suggest that transmission occurs more frequently from badgers to cattle than vice versa (10.4x in the most likely model) and that within-species transmission occurs at higher rates than between-species transmission for both. If representative, our results suggest that control operations should target both cattle and badgers.

Longitudinal dynamics of herd-level Mycobacterium bovis MLVA type surveillance in cattle in Northern Ireland 2003-2016

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.