Risk factors for bovine tuberculosis in low incidence regions related to the movements of cattle

Large scale spatio-temporal modelling of risk factors associated with tuberculosis exposure at the wildlife-livestock interface

The management of animal tuberculosis (TB) is a priority for European Union animal health authorities. However, and despite all the efforts made to date, a significant part of Spain has as yet been unable to obtain the officially tuberculosis-free (OTF) status. Information regarding wildlife disease status is usually scarce, signifying that the role played by wildlife is usually ignored or poorly assessed in large-scale TB risk factor studies. The National Wildlife Health Surveillance Plan in Spain now provides information on infection rates in wildlife reservoirs at a national level, but there are limitations as regards the sample size, the spatio-temporal distribution of the samples, and the lack of homogeneity of the diagnostic techniques employed. The objective of the study described herein was, therefore, to employ a Bayesian approach with the intention of identifying the risk factors associated with four TB rates in cattle: prevalence, incidence, maintenance and persistence in Spain during the period 2014-2019. The modeling approach included highly informative spatio-temporal latent effects with which to control the limitations of the data. Variation partitioning procedures were carried out, and the pure effect of each factor was mapped in order to identify the most relevant factors associated with TB dynamics in cattle in each region. This made it possible to disclose that the movement of cattle, particularly from counties with herd incidence > 1%, was the main driver of the TB dynamics in cattle. The abundance of herds bred for bullfighting was retained in all four models, but had less weight than the movements. After accounting for farm-related factors, the TB prevalence in wild boar was retained in all the models and was significantly related to incidence, maintenance and persistence. With regard to the incidence, variation partitioning revealed that wildlife was the most explicative factor, thus suggesting that it plays a role in the introduction of the pathogen into uninfected herds, and consequently highlighting its importance in breakdowns. These results show, for the first time on a national scale, that wild ungulates play a relevant role in the spatio-temporal variability of TB in cattle, particularly as regards their disease status. Moreover, the spatial representation of the pure effect of each factor made it possible to identify which factors are driving the disease dynamics in each region, thus showing that it is a valuable tool with which to focus efforts towards achieving the OTF status.

Prevalence, distribution, and risk factors of bovine tuberculosis in dairy cattle in central China

Bovine tuberculosis (bTB) is one of the priority epidemic diseases in dairy cattle in China. Continuous surveillance and evaluation of the control programs will help on improving the efficiency of bTB control policy. We designed this study to investigate both animal and herd level prevalence of bTB, as well as to determine the associated factors in dairy farms in Henan and Hubei provinces. A cross-sectional study was conducted from May 2019 to September 2020 in central China (Henan and Hubei provinces). We sampled 40 herds in Henan and six herds in Hubei via stratified systematic sampling and administrated a questionnaire consisting of 35 factors. A total of 4900 whole blood samples were collected from 46 farms, including 545 calves < six months old and 4355 cows ≥ six months old. This study demonstrated a high animal-(18.65%, 95% CI: 17.6-19.8) and herd-level (93.48%, 95%CI: 82.1-98.6) prevalence of bTB in dairy farms in central China. The Least Absolute Shrinkage and Selection Operator (LASSO) and negative binomial regression models showed that herd positivity was associated with the practice of introducing new animals (RR = 1.7, 95%CI: 1.0-3.0, p = 0.042), and changing the disinfectant water in the wheel bath at the farm entrance every three days or less (RR = 0.4, 95%CI: 0.2-0.8, p = 0.005) which reduced the odds of herd positivity. In addition, the result illustrated that testing cows with a higher age group (≥ 60 months old) (OR=1.57, 95%CI: 1.14-2.17, p = 0.006) and within the early stage of lactation (DIM=60-120 days, OR=1.85, 95%CI: 1.19-2.88, p = 0.006) and the later stage of lactation (DIM≥301 days, OR=2.14, 95%CI: 1.30-3.52, p = 0.003) could maximize the odds of detecting seropositive animals. Our results have plenty of benefit to improve bTB surveillance strategies in China and elsewhere in the world. The LASSO and the negative binomial regression models were recommended when dealing with high herd-level prevalence and high dimensional data in questionnaire-based risk studies.

Spatio-temporal models of bovine tuberculosis in the Irish cattle population, 2012-2019

INTRODUCTION

Bovine tuberculosis (bTB) is an important zoonotic disease which has serious and sometimes fatal effects on both human and non-human animals. In many countries it is endemic in the cattle population and has a considerable economic impact through losses in productivity and impacts on trade. The incidence rate in Ireland varies by herd and location and it is hoped that statistical disease-mapping models accounting for both spatio-temporal correlation and covariates might contribute towards explaining this variation.

METHODS

Ireland was divided into equally sized hexagons for computational efficiency (n = 997). Different spatio-temporal random-effects models (e.g. negative binomial Besag-York-Mollié) were explored, using comprehensive data from the national bTB eradication programme to examine the association between covariates and the number of bTB cattle. Leveraging a Bayesian framework, model parameter estimates were obtained using the integrated nested Laplace approximation (INLA) approach. Exceedance probabilities were calculated to identify spatial clusters of cases.

RESULTS

Models accounting for spatial correlation significantly improved model fit in comparison to non-spatial versions where independence between regions was assumed. In our final model at hexagon level, the number of cattle (IR = 1.142, CrI: 1.108 - 1.177 per 1000), the capture of badgers (IR = 5.951, CrI: 4.482 - 7.912), percentage of forest cover (IR = 1.031, CrI: 1.020 - 1.042) and number of farm fragments (IR = 1.012, CrI: 1.009 - 1.015 per 10 fragments) were all associated with an increased incidence of bTB. Habitat suitability for badgers, percentage of dairy herds and the number of cattle movements into the herd were not. As an epidemiological tool and to suggest future work, an interactive online dashboard was developed to monitor disease progression and disseminate results to the general public.

CONCLUSION

Accounting for spatial correlation is an important consideration in disease mapping applications and is often ignored in statistical models examining bTB risk factors. Over time, the same regions in Ireland generally show highest incidences of bTB and allocation of more resources to these areas may be needed to combat the disease. This study highlights national bTB incidence rates. Shifting from national level analysis to smaller geographical regions may help identify localised high-risk areas.

Evaluation of the performance of slaughterhouse surveillance for bovine tuberculosis detection in Castilla y Leon, Spain

Post-mortem inspection (PMI) of routinely slaughtered cattle in abattoirs is an extremely valuable tool for detecting bovine tuberculosis (bTB) infected herds that can supplement active surveillance activities. However, its true performance is difficult to assess due to the multiple factors that may affect it. Here, we determined relative efficiencies in the detection of bTB-compatible lesions and probabilities of subsequent laboratory confirmation of abattoirs located in Castilla y Leon, one of the regions with the largest cattle population in Spain, between 2010 and 2017. The slaughtered animal population was split based on the results of the ante-mortem tests (reactors or non-reactors), and two generalized linear multivariable mixed models were fitted to each subpopulation to calculate the risk of lesion detection and laboratory confirmation per abattoir while accounting for the effect of potential confounding variables. Throughout the 8-year period, ∼30,000 reactors and >2.8 million non-reactor animals in the ante-mortem tests were culled in the abattoirs under study. Bovine TB compatible lesions were detected in 4,710 (16%) reactors and 828 (0.03%) non-reactor animals, of which >95% were confirmed as infected through bacteriology. The probability of disclosure of bTB-like lesions was associated with the animal subpopulation, type of source unit, the herd size, the year of slaughter, the breed and age of the animal, and/or the season of slaughter. The probabilities of detection of bTB-like lesions varied largely depending on the abattoir in both subpopulations, ranging from 603 to 3,070 per 10,000 animals for the reactors and 0.2-16.1 per 10,000 animals for the non-reactor animals. Results obtained here will help to quantify the performance of PMI in abattoirs in Castilla y Leon and the between-abattoir variability, and to identify animals at increased risk of having bTB-like lesions detected during PMI based on animal- and farm-related factors.

Evaluation of Risk Factors Associated With Herds With an Increased Duration of Bovine Tuberculosis Breakdowns in Castilla y Leon, Spain (2010-2017)

The persistence of bovine tuberculosis (bTB) in certain cattle herds is a major concern in countries pursuing disease eradication worldwide. The chronic nature of the disease, the lack of performance of diagnostic tools, and the presence of wildlife reservoirs may lead infected herds to require longer periods to achieve the officially tuberculosis-free (OTF) status. Here, we evaluated the impact of farm and breakdown characteristics on the probability of disease persistence in infected farms in Castilla y Leon, a bTB-endemic region of Spain, using survival and logistic regression models. Data from bTB breakdowns occurring in 3,550 bTB-positive herds detected in 2010–2017 were analyzed. A multivariable Cox proportional hazards model was fitted using time to recover OTF status as the response variable, and a multivariable logistic regression model using the chronic status (yes/no) for herds experiencing particularly long breakdowns as the outcome variable was also used. Both analyses revealed that county-level bTB herd prevalence, herd size, number of incoming animals in the previous 3 years, number of skin test reactors in the disclosing test, and number of days between the disclosing and follow-up tests were associated with increased breakdown duration. Production type was not consistently associated with chronic infection, suggesting that once infected, it is not a significant predictor of outbreak duration beyond the initial stages of the breakdown. Province-level location and number of animals that are bacteriology-positive also affected significantly the expected herd breakdown duration, but their effect became less significant over time. Risk factors identified in this study may help to identify herds more prone to suffer chronic bTB infection that may require additional control measures early on in a breakdown.

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.

Contact chains of cattle farms in Great Britain

Network analyses can assist in predicting the course of epidemics. Time-directed paths or 'contact chains' provide a measure of host-connectedness across specified timeframes, and so represent potential pathways for spread of infections with different epidemiological characteristics. We analysed networks and contact chains of cattle farms in Great Britain using Cattle Tracing System data from 2001 to 2015. We focused on the potential for between-farm transmission of bovine tuberculosis, a chronic infection with potential for hidden spread through the network. Networks were characterized by scale-free type properties, where individual farms were found to be influential 'hubs' in the network. We found a markedly bimodal distribution of farms with either small or very large ingoing and outgoing contact chains (ICCs and OCCs). As a result of their cattle purchases within 12-month periods, 47% of British farms were connected by ICCs to more than 1000 other farms and 16% were connected to more than 10 000 other farms. As a result of their cattle sales within 12-month periods, 66% of farms had OCCs that reached more than 1000 other farms and 15% reached more than 10 000 other farms. Over 19 000 farms had both ICCs and OCCs reaching more than 10 000 farms for two or more years. While farms with more contacts in their ICCs or OCCs might play an important role in disease spread, farms with extensive ICCs and OCCs might be particularly important by being at higher risk of both acquiring and disseminating infections.

Bovine Tuberculosis in Britain and Ireland - A Perfect Storm? the Confluence of Potential Ecological and Epidemiological Impediments to Controlling a Chronic Infectious Disease

Successful eradication schemes for bovine tuberculosis (bTB) have been implemented in a number of European and other countries over the last 50 years. However, the islands of Britain and Ireland remain a significant aberration to this trend, with the recent exception of Scotland. Why have eradication schemes failed within these countries, while apparently similar programs have been successful elsewhere? While significant socio-economic and political factors have been discussed elsewhere as key determinants of disease eradication, here we review some of the potential ecological and epidemiological constraints that are present in these islands relative to other parts of Europe. We argue that the convergence of these potential factors may interact additively to diminish the potential of the present control programs to achieve eradication. Issues identified include heterogeneity of diagnostic testing approaches, the presence of an abundant wildlife reservoir of infection and the challenge of sustainably managing this risk effectively; the nature, size, density and network structure of cattle farming; potential effects of Mycobacterium bovis strain heterogeneity on disease transmission dynamics; possible impacts of concurrent endemic infections on the disclosure of truly infected animals; climatological differences and change coupled with environmental contamination. We further argue that control and eradication of this complex disease may benefit from an ecosystem level approach to management. We hope that this perspective can stimulate a new conversation about the many factors potentially impacting bTB eradication schemes in Britain and Ireland and possibly stimulate new research in the areas identified.

Molecular epidemiology of Mycobacterium tuberculosis complex strains isolated from livestock and wild animals in Italy suggests the need for a different eradication strategy for bovine tuberculosis

Bovine tuberculosis (bTB) is an important zoonosis, which has been re-emerging in different ecological scenarios. In Sicily, Italy, from 2004 to 2014, an anatomopathological survey for tuberculosis-like lesions both in farmed and wild animals was performed. The isolates were genotyped using spoligotyping and Mycobacterial Interspersed Repetitive Units-Variable Number of Tandem Repeats (MIRU-VNTR) techniques. High prevalence of lesions was observed for cattle (4%), pigs (4.9%) and wild boars (6.8%), and a total of 625 Mycobacterium bovis isolates were identified. Genotyping analysis showed the presence of 37 different spoligotypes including fifteen spoligotypes not present in other Italian regions and 266 MIRU-VNTR profiles. Spoligotype SB0120 exhibited the highest prevalence in cattle (50%) and pigs (56%) and the highest genetic variety with 126 different MIRU-VNTR profiles. The isolation of M. bovis in a farmer underlines the importance of M. bovis identification during the human TB diagnostic processes. This study supported the use of the genotyping analysis as a valuable tool for the evaluation of the epidemiological role of pigs and other domestic reservoirs such as goats and the role of wildlife in the maintenance of bTB infection.

A review of risk factors for bovine tuberculosis infection in cattle in the UK and Ireland

Bovine tuberculosis (bTB) is an important disease of cattle caused by infection withMycobacterium bovis, a pathogen that may be extremely difficult to eradicate in the presence of a true wildlife reservoir. Our objective was to identify and review relevant literature and provide a succinct summary of current knowledge of risk factors for transmission of infection of cattle. Search strings were developed to identify publications from electronic databases to February 2015. Abstracts of 4255 papers identified were reviewed by three reviewers to determine whether the entire article was likely to contain relevant information. Risk factors could be broadly grouped as follows: animal (including nutrition and genetics), herd (including bTB and testing history), environment, wildlife and social factors. Many risk factors are inter-related and study designs often do not enable differentiation between cause and consequence of infection. Despite differences in study design and location, some risk factors are consistently identified, e.g. herd size, bTB history, presence of infected wildlife, whereas the evidence for others is less consistent and coherent, e.g. nutrition, local cattle movements. We have identified knowledge gaps where further research may result in an improved understanding of bTB transmission dynamics. The application of targeted, multifactorial disease control regimens that address a range of risk factors simultaneously is likely to be a key to effective, evidence-informed control strategies.

Role of Cattle Movements in Bovine Tuberculosis Spread in France between 2005 and 2014

Live animal movements are a major transmission route for the spread of infectious agents such as Mycobacterium bovis, the main agent of bovine Tuberculosis (bTB). France became officially bTB-free in 2001, but M. bovis is still circulating in the cattle population, with about a hundred of outbreaks per year, most located in a few geographic areas. The aim of this study was to analyse the role of cattle movements in bTB spread in France between 2005 and 2014, using social network analysis and logistic regression models. At a global scale, the trade network was studied to assess the association between several centrality measures and bTB infection though a case-control analysis. The bTB infection status was associated with a higher in-degree (odds-ratio [OR] = 2.4 [1.1–5.4]) and with a higher ingoing contact chain (OR = 2.2 [1.0–4.7]). At a more local scale, a second case-control analysis was conducted to estimate the relative importance of cattle movements and spatial neighbourhood. Only direct purchase from infected herds was shown to be associated with bTB infection (OR = 2.9 [1.7–5.2]), spatial proximity to infected herds being the predominant risk factor, with decreasing ORs when distance increases. Indeed, the population attributable fraction was 12% [5%–18%] for cattle movements and 73% [68%–78%] for spatial neighbourhood. Based on these results, networks of potential effective contacts between herds were built and analysed for the three major spoligotypes reported in France. In these networks, the links representing cattle movements were associated with higher edge betweenness than those representing the spatial proximity between infected herds. They were often links connecting distinct communities and sometimes distinct geographical areas. Therefore, although their role was quantitatively lower than the one of spatial neighbourhood, cattle movements appear to have been essential in the French bTB dynamics between 2005 and 2014.

Should they stay, or should they go? Relative future risk of bovine tuberculosis for interferon-gamma test-positive cattle left on farms

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is a serious infectious disease that remains an ongoing concern for cattle farming worldwide. Tuberculin skin-tests are often used to identify infected animals (reactors) during test-and-cull programs, however, due to relatively poor sensitivity, additional tests can be implemented in parallel. For example, in Northern Ireland interferon-gamma (IFN-g) testing is used in high-risk herds. However, skin-test negative animals which are positive to the IFN-g test are not required by law to be slaughtered – therefore the final choice for these animals’ fate is left with the owner. During this study we investigated whether these animals represented a greater risk of becoming a skin reactor, relative to IFN-g test negative animals from the same herds. Our study population included 1107 IFN-g positive animals from 239 herds. A Cox-proportional hazard model indicated that animals which tested IFN-g positive were 2.31 times (95% CI: 1.92-2.79; P < 0.001) more likely to become a reactor compared with IFN-g negative animals. Animals from dairy herds, and from herds in the south-east, were of higher risk than animals from beef herds and other regions, respectively. Our findings suggest that IFN-g positive animals represent a higher risk of failing a skin-test in the future, indicating the value of IFN-g testing for identifying early-stage infected animals. These IFN-g positive animals are not under any disease restriction, and may move freely (trade), which may put recipient herds at increased risk. Our findings provide important evidence for stakeholders engaged in bTB eradication programs.

Estimating epidemiological parameters for bovine tuberculosis in British cattle using a Bayesian partial-likelihood approach

Fitting models with Bayesian likelihood-based parameter inference is becoming increasingly important in infectious disease epidemiology. Detailed datasets present the opportunity to identify subsets of these data that capture important characteristics of the underlying epidemiology. One such dataset describes the epidemic of bovine tuberculosis (bTB) in British cattle, which is also an important exemplar of a disease with a wildlife reservoir (the Eurasian badger). Here, we evaluate a set of nested dynamic models of bTB transmission, including individual- and herd-level transmission heterogeneity and assuming minimal prior knowledge of the transmission and diagnostic test parameters. We performed a likelihood-based bootstrapping operation on the model to infer parameters based only on the recorded numbers of cattle testing positive for bTB at the start of each herd outbreak considering high- and low-risk areas separately. Models without herd heterogeneity are preferred in both areas though there is some evidence for super-spreading cattle. Similar to previous studies, we found low test sensitivities and high within-herd basic reproduction numbers (R₀), suggesting that there may be many unobserved infections in cattle, even though the current testing regime is sufficient to control within-herd epidemics in most cases. Compared with other, more data-heavy approaches, the summary data used in our approach are easily collected, making our approach attractive for other systems.