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

First time whole genome sequencing of Mycobacterium bovis from the environment supports transmission at the animal-environment interface

Spreading of Mycobacterium bovis causing animal tuberculosis (TB) at livestock-wildlife-environment interfaces remains a significant problem. Recently, we provided evidence of widespread environmental contamination of an endemic animal TB setting with viable and dormant M. bovis cells able to recover metabolic activity, making indirect transmission via environmental contamination plausible. We now report the first whole genome sequences of M. bovis recovered from the environment. We establish epidemiological links at the environment-animal interface by phylogenomic comparison of these M. bovis genomes with those isolated from livestock and wild ungulates from the same area. Environmental and animal genomes are highly intertwined and distribute similarly into the same M. bovis lineages, supporting several instances of environmental contamination. This study provides compelling evidence of M. bovis excretion into the environment and viability maintenance, supporting the environment as a potential source of new infection. These insights have clear implications for policy formulation, advocating environmental surveillance and an ecosystem perspective in TB control programs. ENVIRONMENTAL IMPLICATION: We report the first whole genome sequences of M. bovis from the environment and establish epidemiological links at the environment-animal interface, demonstrating close phylogenomic relatedness of animal and environmental M. bovis. Definitive evidence of M. bovis excretion into the environment with viability maintenance is provided, supporting the environment as a potential source of new infection. Implications of this work include methodological innovations offering a tool to resolve indirect transmission chains and support customized biosecurity measures. Policy formulation aiming at the control of animal tuberculosis and cost mitigation should consider these findings, encouraging environmental surveillance in official eradication programmes.

A scoping review on bovine tuberculosis highlights the need for novel data streams and analytical approaches to curb zoonotic diseases

Zoonotic diseases represent a significant societal challenge in terms of their health and economic impacts. One Health approaches to managing zoonotic diseases are becoming more prevalent, but require novel thinking, tools and cross-disciplinary collaboration. Bovine tuberculosis (bTB) is one example of a costly One Health challenge with a complex epidemiology involving humans, domestic animals, wildlife and environmental factors, which require sophisticated collaborative approaches. We undertook a scoping review of multi-host bTB epidemiology to identify trends in species publication focus, methodologies, and One Health approaches. We aimed to identify knowledge gaps where novel research could provide insights to inform control policy, for bTB and other zoonoses. The review included 532 articles. We found different levels of research attention across episystems, with a significant proportion of the literature focusing on the badger-cattle-TB episystem, with far less attention given to tropical multi-host episystems. We found a limited number of studies focusing on management solutions and their efficacy, with very few studies looking at modelling exit strategies. Only a small number of studies looked at the effect of human disturbances on the spread of bTB involving wildlife hosts. Most of the studies we reviewed focused on the effect of badger vaccination and culling on bTB dynamics with few looking at how roads, human perturbations and habitat change may affect wildlife movement and disease spread. Finally, we observed a lack of studies considering the effect of weather variables on bTB spread, which is particularly relevant when studying zoonoses under climate change scenarios. Significant technological and methodological advances have been applied to bTB episystems, providing explicit insights into its spread and maintenance across populations. We identified a prominent bias towards certain species and locations. Generating more high-quality empirical data on wildlife host distribution and abundance, high-resolution individual behaviours and greater use of mathematical models and simulations are key areas for future research. Integrating data sources across disciplines, and a "virtuous cycle" of well-designed empirical data collection linked with mathematical and simulation modelling could provide additional gains for policy-makers and managers, enabling optimised bTB management with broader insights for other zoonoses.

Intra- and interspecies infectious neighbourhoods as determinant parameters for Mycobacterium bovis infection among badgers in southwestern France

The epidemiological system for Mycobacterium bovis in France involves cattle and, in some areas, wildlife species (mainly badgers and wild boar). This multi-host aspect complicates the control and eradication prospects for bovine tuberculosis in endemic areas, despite the surveillance and control measures implemented for decades in this officially tuberculosis-free European country. To improve control measures, and to manage spillback transmission from badgers to cattle, it is necessary to clarify the transmission mechanisms of M. bovis in these epidemiological systems. We modelled a badger population from a southwestern endemic area by a Dirichlet tessellation based on a sett census conducted by local hunters and trappers between 2013 and 2015. We then used a logistic regression model to test the association between the infection status of setts and computed variables depicting three types of transmission (intraspecific, interspecific and landscape-associated). The apparent prevalence of infected setts was of 40.5%. Two variables were significantly associated with the probability for a sett to be infected: the proportion of neighbouring setts that were infected (OR: 3.19 [2.04-5.17]95%) and the presence of nearby pastures belonging to an infected farm (OR: 2.33 [1.13-4.89]95%]. While badger culling measures have been implemented according to the national TB control plan in the study area since 2012 (in the vicinity of infected farms and their pastures), our results clearly highlight the need to reinforce measures aimed at reducing both intraspecific and interspecific infection pressure. For this purpose, the promising prospect of badger vaccination could be considered, along with biosecurity measures.

Genomic epidemiology sheds light on the emergence and spread of Mycobacterium bovis Eu2 Clonal Complex in Portugal

ABSTRACTAnimal tuberculosis (TB) remains a serious concern for animal and human health. Mycobacterium bovis circulates in multi-host systems, dominated by the European 2 clonal complex (Eu2) in Iberia. In this work, we use genomic epidemiology to infer the emergence, spread, and spatiotemporal patterns of Eu2 in the official epidemiological risk area of animal TB in Portugal. Phylogenetic analysis of 144 M. bovis whole-genome sequences from cattle, wild boar, and red deer, representing the 2002-2021 period, distinguished three Eu2 clades that evolved independently. The major Eu2 clade underwent phylodynamic inferences to estimate the time and location of outbreaks, host transitions, and spatial diffusion as well. The origin of this Eu2 clade was attributed to the red deer population in the Castelo Branco district, near the border with Spain. Most host transitions were intraspecific (80%), while interspecific transmissions between wildlife species (wild boar-red deer), and between wild boar and cattle, were highly supported. Phylogeographic reconstruction evidenced that most transitions (82%) occur within municipalities, highlighting local transmission corridors.Our study indicates that M. bovis continues to spread at the cattle-wildlife interface within the animal TB hotspot area, possibly driven by the foraging behaviour of wild boar near agricultural lands. Red deer seems to be an important driver of TB within wildlife hosts, while the wild boar links the multi-host wildlife community and livestock. This work highlights the value of combining genomic epidemiology with phylodynamic inference to resolve host jumps and spatial patterns of M. bovis, providing real-time clues about points of intervention.

Improving the communication between farmers and veterinarians to enhance the acceptability of bovine tuberculosis eradication programmes

France and Spain have been fighting against bovine tuberculosis (bTB) for years, even though new outbreaks continue to appear on both sides of the border, generating misconceptions about the disease and social distrust in the eradication programme and competent authorities. The perceived disease risk and the commitment of all interested parties are key factors for the successful implementation of control programmes, as they might influence the acceptability of recommended measures. Effective communication can contribute to increasing knowledge, trust and stakeholders' engagement, thus ensuring the acceptability of the eradication programme. This study was conducted in Catalonia (Spain) and Pyrenees-Atlantiques (France) in the frame of the INNOTUB project (https://innotub.eu/) to characterise the communication on bTB in the trans-Pyrenees region and provide recommendations to improve it. The communication on bTB was characterised by analysing 153 (Spain) and 66 (France) online freely available texts, published between 2018 and 2020, through Content Analysis and Critical Metaphor Analysis. Moreover, six farmers and four veterinarians were in-depth interviewed in each area to gather information about the communication on bTB. Interviews were made in original languages and analysed using a qualitative thematic approach. A pilot participatory intervention inspired by the Systematic Tool for Behavioural Assumption Validation and Exploration (STAVE) method was used to develop a list of proposals to improve communication and to promote the creation of territorial networks/committees on bTB prevention and control. It included three focus groups with farmers and veterinarians, a meeting with representatives of the regional veterinary services, and a final deliberative workshop. Results highlight the existence of a controversial debate on bTB and a heterogeneous understanding between stakeholders. Institutional and scientific communication mainly focus on bTB detection and control while other aspects are left in the background. On the contrary, farmers extend their communication to a greater variety of topics. The metaphorical framing strongly differed among actors, while veterinary services and researchers "fight" against bTB and "progress" toward the eradication, farmers place themselves in a framework of "sacrifice" and, particularly in Spain, they play a passive role. The proposals developed by the participants to improve the current communication on bTB included: (i) create participatory meeting spaces to share opinions and information; (ii) improve data accessibility (on epidemiological situations); (iii) develop clearer and written protocols and informative visual material; (iv) redesign the training courses (v) increase the stakeholders' participation in the design of protocols.

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.

Animal tuberculosis control in a disease-free country, France: does the long and winding road really lead to eradication?

It took France almost fifty years to attain its officially animal tuberculosis (TB) free status in 2000, granting the country a favourable position for international live animal trading. The initial TB control program has been adapted at different times in its history in order to suit changing epidemiological contexts: it was first focused on detection and elimination of infected animals while later on protecting TB free herds became a priority.In spite of all the efforts put into the program, final eradication has still not been achieved. Instead, the eradication process has stalled, most probably due to changes in breeding practices in the last 30 years. Indeed, the beef industry has overtaken the milk industry, which has led to the occurrence of new TB risks. Novel epidemiological situations in some regions of extensive beef cattle farming, where wildlife species (wild boar, badger) are also infected, have emerged. More adapted measures have thus been implemented, progressively evaluated and improved in order to reinforce prevention of infection, to follow up with the eradication goal and to strengthen, coordinate and re-motivate field resources. These include, among others, introduction of biosecurity measures in the herd, risk based surveillance and management of wildlife and cattle, improvement of screening in the field and at the abattoir, better diagnosis, but also improvement of communication, awareness, training activities of the main field actors. Very importantly, this new plan has been established through the participation of the majority of involved stakeholders -the farmer industry, hunter associations, veterinarians, scientists and the government-, through coordinated specific steering committees and ad hoc working groups.Without doubt, the main challenge for the next few years is reinforcing communication to encourage and strengthen the program in an already faltering agro-social system. In addition, it will be essential to continue sustaining national research and international collaborations to feed the program with relevant scientific data enabling the authorities to undertake the most pertinent measures for tackling the disease in the short term.

Once bitten twice shy: Risk factors associated with bovine tuberculosis recurrence in Castilla y Leon, Spain

Persistence of bovine tuberculosis (bTB) in cattle herd remains a major challenge in disease elimination due to the ineffectual removal of all infected animals in a bTB breakdown. Characterization of herds with a higher probability of experiencing further bTB breakdowns can help to implement specific risk-based policies for disease control and eradication. Here, our aim was to identify herd- and breakdown-level risk factors in bTB infected herds in Castilla y Leon, Spain, associated with a decreased time to recurrence and an increased risk of recurrence using a mixed effects Cox proportional hazards model and a multivariable logistic regression model, respectively. Results revealed that location (province), herd size and number of incoming animals/contacts were good predictors of a decreased time to bTB recurrence and an increased risk of becoming a recurrent herd. Additionally, the duration of the previous outbreak and the number of IFN-γ herd-tests applied in it were associated with increased odds of (an early) recurrence. Risk factors identified here can be used for early identification of herds in which bTB eradication may be more challenging and that should thus be subjected to increased control efforts. The characterization of high-risk herds may help to minimize the risk of reinfection and emphasize early detection and removal of bTB positive animals in the herd.

Descriptive network analysis and the influence of timescale on centrality and cohesion metrics from a system of between-herd dairy cow movements in Ontario, Canada

Previous research has demonstrated that static monthly networks of between-herd dairy cow movements in Ontario, Canada were highly fragmented, reducing potential for large-scale outbreaks. Extrapolating results from static networks can become problematic for diseases with an incubation period that exceeds the timescale of the network. The objectives of this research were to: 1) describe the networks of dairy cow movements in Ontario, and 2) describe the changes that occur among network analysis metrics when conducted at seven different timescales. Networks of dairy cow movements were created using Lactanet Canada milk recording data collected in Ontario between 2009 and 2018. Centrality and cohesion metrics were calculated after aggregating the data at seven timescales: weekly, monthly, semi-annual, annual, biennial, quinquennial, and decennial. There were 50,598 individual cows moved between Lactanet-enrolled farms, representing approximately 75% of provincially registered dairy herds. Most movements occurred over short distances (median = 39.18 km), with fewer long-range movements (maximum = 1150.80 km). The number of arcs increased marginally relative to the number of nodes with longer network timescales. Both mean out-degree, and mean clustering coefficients increased disproportionately with increasing timescale. Conversely, mean network density decreased with increasing timescale. The largest weak and strong components at the monthly timescale were small relative to the full network (267 and 4 nodes), whereas yearly networks had much higher values (2213 and 111 nodes). Higher relative connectivity in networks with longer timescales suggests pathogens with long incubation periods and animals with subclinical infection present increased potential for wide-spread disease transmission among dairy farms in Ontario. Careful consideration of disease-specific dynamics should be made when using static networks to model disease transmission among dairy cow populations.

Geo-epidemiology of animal tuberculosis and Mycobacterium bovis genotypes in livestock in a small, high-incidence area in Sicily, Italy

Introduction

The persistence of animal tuberculosis (TB) in livestock is a major concern in Sicily, Italy. The objective of this study was to elucidate the transmission dynamics of M. bovis infection in a highly circumscribed, and at the same time geographically diverse, high-risk area of the island through an in-depth geo-epidemiological investigation of TB in cattle and black pigs raised in small-scale extensive farms across the district of Caronia.

Methods

We used genotype analysis coupled with geographic information system (GIS) technology and phylogenetic inference to characterize the spatial distribution of TB and M. bovis genotypes in livestock and the genetic relationships between M. bovis isolates. A total of 589 M. bovis isolates collected from slaughtered cattle (n = 527) and Sicilian black pigs (n = 62) over a 5-year period (2014–2018) were included in the study.

Results

TB was widespread throughout the district and was most frequent in the north-central area of the district, especially along one of the district’s streams. We identified a total of 62 M. bovis genotypes. Identical genetic profiles were isolated from both neighboring and non-neighburing herds. The 10 most frequent genotypes, accounting for 82% of M. bovis isolates, showed geographic specificities in that they tended to cluster in specific spatial niches. The landscape structure of these niches—i.e. steep slopes, rocky ridges, meadows and streams—is likely to have had a significant influence on the distribution of TB among livestock in Caronia. Higher concentrations of TB were observed along streams and in open meadows, while rocky ridges and slopes appeared to have hampered the spread of TB.

Discussion

The geographical distribution of TB cases among livestock in Caronia is consistent with several epidemiological scenarios (e.g., high density of infected herds along the streams or in hilly plateau where livestock share pastures). Landscape structure is likely to play an important role in the transmission and persistence of M. bovis infection across the district. Additional potential risk factors, such as livestock trading and extensive breeding methods, are also discussed. Our results will contribute to the improvement of surveillance, control and eradication activities of TB in Sicily by the implementation of ad hoc TB control measures, especially in farms located along streams, sharing common pastures or with mixed animal species.

Region-wise analysis of beef cow movements in Japan

Animal movement is an important factor in the transmission of animal infectious diseases. A better understanding of movement patterns is therefore necessary for developing effective control measures against disease spread. In Japan, a cattle tracing system was established in 2003, following a bovine spongiform encephalopathy epidemic, and the information on all cattle movements has been stored in a national database maintained by the National Livestock Breeding Center. Using these data, we previously analyzed the movement of dairy cows, concluding that heterogeneities in cattle movement are associated with regional and seasonal factors. In the present study, we aimed to identify specific factors affecting the regional and seasonal movement patterns of beef cows in Japan. From April 2012 to March 2017, 797,553 farm-to-farm movement events were recorded. We analyzed movements by month and by cattle age and looked at the frequency of movement within and between seven regions spanning the national territory. Our results show that calf movement peaked at 9-10 months old; these movements were considered to be via the market and were frequent within and between regions. For inter-regional movements, Kyushu region was the top producer of calves for calf trading markets throughout Japan. With regard to intra-regional movements, round-trip movements for summer grazing were observed in May and October for cattle of various ages in the northern regions, especially Hokkaido and Tohoku. Moreover, the movements of Japanese Shorthorn breeds in Tohoku region exhibited consistent annual peaks in May and October/November, in accordance with their seasonal breeding practice. In the areas with high relative densities of dairy cows, such as Hokkaido, the shipping of newborn beef calves produced via embryo transfer to dairy cows was also observed. Overall, understanding the patterns of beef cow movement will help develop effective disease surveillance measures, such as pre-movement inspections focused on specific regions and types of movement.

"BACACIX", a spatial index combining proxies of bovine and badger space use associated with extended Mycobacterium bovis circulation in France

To better prevent and control multi-host pathogen circulation over large areas, it is essential to identify patterns of disease persistence within host communities involved in pathogen circulation at a macroscale. The aim of this study was to design and calculate "BACACIX", a spatial index of indirect contacts between cattle and badgers, two species involved in the circulation of Mycobacterium bovis, one of the main causative agents of bovine tuberculosis (bTB), in some areas of France. The index combined spatial models of land use distribution (the probable distribution defining animal use of space) based on pasture location for cattle, and based on land cover for badgers, with proxies for animal density for both species. For badgers, we used two series of census data of badger setts in two regions of France to evaluate our model of badger space use distribution (also known as utilization distribution), and analyzed the relationship between BACACIX and the upsurge of bovine tuberculosis observed in several regions of France during the decade after the country obtained the officially bTB-free status in 2001. We observed high values of BACACIX from the southwest to the northeast of France and from Brittany to the Channel coast. Conversely, in two areas (north-central area and Mediterranean coast), index values were low, suggesting that indirect cattle-badger contacts were unlikely. In the two series of census data of badger setts that we analyzed, 96.5% and 87% of the global positioning system (GPS) locations of badger setts, respectively were located in the calculated badger space use distribution. A logistic regression model showed that after controlling bTB over the previous decade, the value of the index was positively associated with the risk of cattle outbreaks between 2001 and 2010 (OR = 1.57). In addition, the risk of bTB occurrence in cattle decreased when the pasture area outside the badger space use distribution increased. In the future, the spatial index of indirect cattle-badger contacts we propose could help to better target bTB surveillance and control in France.

Can Ingoing Contact Chains and other cattle movement network metrics help predict herd-level bovine tuberculosis in Irish cattle herds?

We used logistic regression to investigate whether the risk of an Irish cattle herd undergoing a bovine tuberculosis (bTB) breakdown increased with the size of the Ingoing Contact Chain (ICC) of previous herd to herd cattle movements, in a sequence up to eight moves back from the most recent, direct, movement into the herd. We further examined whether taking into account the bTB test history of each herd in the chain would improve model fit. We found that measures of cattle movements directly into the herd were risk factors for subsequent bTB restrictions, and the number of herds that animals were coming from was the most important of these. However, in contrast to a previous study in Great Britain, the ICC herd count at steps more remote than direct movements into the herd did not result in better fitting models than restricting the count to direct movements. Restricting the ICC counts to herds which had previously or would in the future test positive for bTB resulted in improved model fits, but this was not the case if only the previous test status was considered. This suggests that in many cases bTB infected animals are moving out of herds before being identified through testing, and that risk-based trading approaches should not rely solely on the previous test history of source herds as a proxy for future risk. Model fit was also improved by the inclusion of variables measuring bTB history of the herd, bTB in neighbouring herds, herd size, herd type, the movement network measures "in strength" and "betweenness", altitude, modelled badger abundance and county. Rainfall was not a good predictor. The most influential measures of bTB in nearby herds (a proxy for neighbourhood infection) were the proportion of herds with a history of bTB whose centroids were within 6 km, or whose boundaries were within 4 km, of the index herd. As well as informing national control and surveillance measures, our models can be used to identify areas where bTB rates are anomalously high, to prompt further investigation in these areas.

Bovine tuberculosis in youngstock cattle: A narrative review

Bovine tuberculosis (bTB), caused by Mycobacterium bovis, remains a high-priority global pathogen of concern. The role of youngstock animals in the epidemiology of bTB has not been a focus of contemporary research. Here we have aimed to collate and summarize what is known about the susceptibility, diagnosis, transmission (infectiousness), and epidemiology to M. bovis in youngstock (up to 1-year of age). Youngstock are susceptible to M. bovis infection when exposed, with the capacity to develop typical bTB lesions. Calves can be exposed through similar routes as adults, via residual infection, contiguous neighborhood spread, wildlife spillback infection, and the buying-in of infected but undetected cattle. Dairy systems may lead to greater exposure risk to calves relative to other production systems, for example, via pooled milk. Given their young age, calves tend to have shorter bTB at-risk exposure periods than older cohorts. The detection of bTB varies with age when using a wide range of ante-mortem diagnostics, also with post-mortem examination and confirmation (histological and bacteriological) of infection. When recorded as positive by ante-mortem test, youngstock appear to have the highest probabilities of any age cohort for confirmation of infection post-mortem. They also appear to have the lowest false negative bTB detection risk. In some countries, many calves are moved to other herds for rearing, potentially increasing inter-herd transmission risk. Mathematical models suggest that calves may also experience lower force of infection (the rate that susceptible animals become infected). There are few modeling studies investigating the role of calves in the spread and maintenance of infection across herd networks. One study found that calves, without operating testing and control measures, can help to maintain infection and lengthen the time to outbreak eradication. Policies to reduce testing for youngstock could lead to infected calves remaining undetected and increasing onwards transmission. Further studies are required to assess the risk associated with changes to testing policy for youngstock in terms of the impact for within-herd disease control, and how this may affect the transmission and persistence of infection across a network of linked herds.

Evidence, Challenges, and Knowledge Gaps Regarding Latent Tuberculosis in Animals

Mycobacterium bovis and other Mycobacterium tuberculosis complex (MTBC) pathogens that cause domestic animal and wildlife tuberculosis have received considerably less attention than M. tuberculosis, the primary cause of human tuberculosis (TB). Human TB studies have shown that different stages of infection can exist, driven by host–pathogen interactions. This results in the emergence of heterogeneous subpopulations of mycobacteria in different phenotypic states, which range from actively replicating (AR) cells to viable but slowly or non-replicating (VBNR), viable but non-culturable (VBNC), and dormant mycobacteria. The VBNR, VBNC, and dormant subpopulations are believed to underlie latent tuberculosis (LTB) in humans; however, it is unclear if a similar phenomenon could be happening in animals. This review discusses the evidence, challenges, and knowledge gaps regarding LTB in animals, and possible host–pathogen differences in the MTBC strains M. tuberculosis and M. bovis during infection. We further consider models that might be adapted from human TB research to investigate how the different phenotypic states of bacteria could influence TB stages in animals. In addition, we explore potential host biomarkers and mycobacterial changes in the DosR regulon, transcriptional sigma factors, and resuscitation-promoting factors that may influence the development of LTB.

A mechanistic model captures livestock trading, disease dynamics, and compensatory behaviour in response to control measures

Trade is a complex, multi-faceted process that can contribute to the spread and persistence of disease. We here develop novel mechanistic models of supply. Our model is framed within a livestock trading system, where farms form and end trade partnerships with rates dependent on current demand, with these trade partnerships facilitating trade between partners. With these time-varying, stock dependent partnership and trade dynamics, our trading model goes beyond current state of the art modelling approaches. By studying instantaneous shocks to farm-level supply and demand we show that behavioural responses of farms lead to trading systems that are highly resistant to shocks with only temporary disturbances to trade observed. Individual adaptation in response to permanent alterations to trading propensities, such that animal flows are maintained, illustrates the ability for farms to find new avenues of trade, minimising disruptions imposed by such alterations to trade that common modelling approaches cannot adequately capture. In the context of endemic disease control, we show that these adaptations hinder the potential beneficial reductions in prevalence suTrade is a complex, multi-faceted process that can contribute to the spread and persistence of disease. We here develop novel mechanistic models ofch changes to trading propensities have previously been shown to confer. Assessing the impact of a common disease control measure, post-movement batch testing, highlights the ability for our model to measure the stress on multiple components of trade imposed by such control measures and also highlights the temporary and, in some cases, the permanent disturbances to trade that post-movement testing has on the trading system.

Evaluation of the discriminatory power of spoligotyping and 19-locus mycobacterial interspersed repetitive unit-variable number of tandem repeat analysis (MIRU-VNTR) of Mycobacterium bovis strains isolated from cattle in Algeria

Bovine tuberculosis (bTB) caused by Mycobacterium (M.) bovis and M. caprae is a transmissible disease of livestock, notifiable to the World Organization for Animal Health (OIE). BTB particularly affects cattle and small ruminants and can be transmitted to humans thereby posing a significant threat to veterinary and public health worldwide. M. bovis is the principal cause of bTB in Algeria. In order to better understand the route of spreading and elaborate an eradication program, isolation and characterization of mycobacteria from Algerian cattle was performed. Sixty strains belonging to the M. tuberculosis complex were analyzed by spoligotyping, thereof 42 by 19-locus-MIRU-VNTR-typing. Spoligotyping revealed 16 distinguishable patterns (Hunter-Gaston discriminatory index [HGDI] of 0.8294), with types SB0120 (n = 20) and SB0121 (n = 13) being the most frequent patterns, representing 55% of the strains. Analyses based on 19-locus-MIRU-VNTR yielded 32 different profiles, five clusters and one orphan pattern, showing higher discriminatory power (HGDI = 0.9779) than spoligotyping. Seven VNTR-loci [VNTR 577 (alias ETR C), 2163b (QU11b), 2165 (ETR A), 2461 (ETR B), 3007 (MIRU 27), 2163a (QUB11a) and 3232 (QUB 3232)] were the most discriminative loci (HGDI ˃ 0.50). In conclusion, 19-locus-MIRU-VNTR yielded more information than spoligotyping concerning molecular differentiation of strains and better supports the elucidation of transmission routes of M. bovis between Algerian cattle herds.

Region-wise analysis of dairy cow movements in Japan

BACKGROUND

Animal movement is considered the most significant factor in the transmission of infectious diseases in livestock. A better understanding of its effects would help provide a more reliable estimation of the disease spread and help develop effective control measures. If the movement pattern is heterogeneous, its characteristics should be considered in epidemiological analyses, such as when using simulation models to obtain reliable outputs. In Japan, following the bovine spongiform encephalopathy epidemic, a traceability system for cattle was established in 2003, and the registration of all cattle movements in the national database began. This study is the first to analyze cattle movements in Japan. We examined regional and seasonal heterogeneity in dairy cow movements, which accounted for most Japanese breeding cattle.

RESULTS

In the 14 years from April 2005 to March 2018, 4,577,709 between-farm movements of dairy cows were recorded, and the number of movements was counted by month and age for both inter- and intra-regional movements. As a result, two characteristic round-trip movements were observed: one was non-seasonal and inter-regional movements related to cattle-breeding ranches in Hokkaido (the northern region of Japan), which consists of the movement of cows around ages 6 to 8 and 21 to 23 months old. In addition, the seasonal movement of heifers for summer grazing within Hokkaido occurred in May and October at the peak ages of 13 to 14 and 19 to 20 months old, respectively. The observed heterogeneity seemed to reflect the suitability of raising the Holstein breed in Hokkaido and the shortage of supply of replacement heifers and available farming areas outside Hokkaido.

CONCLUSIONS

Understanding the patterns of dairy cow movements will help develop reliable infectious disease models and be beneficial for developing effective control measures against these diseases.

Quantitative decision making in animal health surveillance: Bovine Tuberculosis Surveillance in Belgium as case study

Despite eradication and control measures applied across Europe, bovine tuberculosis (bTB) remains a constant threat. In Belgium, after several years of official bTB-free status, routine movement testing, as currently practiced, revealed itself inadequate to detect some herds affected by sporadic breakdowns. The aim of this study was to assess different surveillance system components that strike a balance between cost and effectiveness and to identify sustainable alternatives, which substantiate a bTB-free claim while ensuring early detection and acceptance by various animal health stakeholders. For this pupose, a stochastic iteration model was used to simulate the current surveillance system's expected performance in terms of detection sensitivity and specificity. These results were then descriptively compared with observed field results. Second, the cost and effectiveness of simulated alternative surveillance components were quantified. Sensitivity analyses were performed to measure key assumptions' impacts (i.e. regarding diagnostic tests and true prevalence). The results confirmed discrepancies between the observed and simulated expected performance of bTB surveillance in Belgium. Second, simulated alternatives showed that interferon gamma (IFN-γ) and serological testing with antibody-enzyme linked immunosorbent assay (Ab-ELISA) targeting at-risk herds would enable an increase in the overall cost effectiveness (sensitivity and specificity) of the Belgian bTB surveillance system. Sensitivity analyses showed that results remained constant despite the modification of some key assumptions. While the performance of the ongoing bTB surveillance system in Belgium was questionable at the time of the study, this exercise highlighted that not only sensitivity but specificity also are key drivers of surveillance performance. The quantitative approach, taking into consideration various stakeholders' needs and priorities, revealed itself to be a useful tool in allowing evidence-based decision making for future tuberculosis surveillance in Belgium, in line with the international standards.

Sensitivity of bovine tuberculosis surveillance through intradermal tests in cattle in France: An evaluation of different scenarios

The current situation regarding bovine tuberculosis (bTB) in Europe is spatially heterogeneous, with stagnating or increasing trends in bTB prevalence in many European regions, underlying the challenge in controlling this disease. In France, in spite of the implementation of two control programs in 2010-2012 to eradicate the disease and maintain the bTB-free status, bTB prevalence has continued to increase, underlying the need to reinforce and adapt surveillance measures. The goal of this study was to evaluate the effectiveness of bTB surveillance in high-risk areas in metropolitan France, with an emphasis on the criteria to select herds and animals within herds in the context of programmed surveillance and movement testing. The fraction of bTB-infected herds detected by the surveillance was quantified using a stochastic scenario tree modelling approach, with input parameter values based on surveillance and cattle traceability data and literature. The detection fraction was assessed for the current surveillance system and for alternative scenarios. The model predicted that the median detection fraction of infected herds by the current programmed surveillance in high-risk areas, which consists in annual testing of herds with a minimum age of testing of 24 months, was 71.5 % (interquartile interval: 47.4-89.4). The results showed a significant gain of the detection fraction with a decrease from 24 to 12 months old (83.5 % [60.6-95.9]) or to six weeks old (91.3 % [71.6-99.0]). Regarding pre-movement surveillance, tests are currently mandatory for bovines that originate from a previously infected herd or from a herd epidemiologically linked to a bTB-infected herd. The median detection fraction predicted by the model for this surveillance scenario was 1.2 % [0.7-1.8]. For the alternative scenario, where surveillance would be extended to all herds in high-risk areas, the model predicted a significant increase of the detection fraction to 26.5 % [18.1-37.9]. The results were sensitive to the following input values: the number of infected bovines within herds and, to a lower extent, the comparative intradermal tuberculin test sensitivity for both models, and surveillance coverage for the model on pre-movement surveillance. Our study underlines several complementary ways to improve the detection of infected herds, which is critical for implementing control measures and epidemiological investigations as early as possible. These necessary changes in surveillance must be accompanied by a global reflexion on surveillance financing.

Relative Contribution of Each Component of the French Ante-Mortem Surveillance System for Bovine Tuberculosis in Its Overall Sensitivity

The aim of this study was to assess the contribution to the sensitivity of the French ante-mortem surveillance system for bovine tuberculosis in cattle of each of the system’s components (periodic screening, epidemiological investigations, and screening exchanged animals), on a local scale defined by administrative areas. These components were individually assessed in previous studies by scenario tree modeling. We used scenario tree modeling at the herd level and combined the results to evaluate the overall sensitivity of the ante-mortem surveillance system. The probability to detect at least one infected herd was consistent with the location of the outbreaks detected in 2016. In areas with a high apparent incidence, the probability of an infected herd to be detected was satisfactory (for an infected herd there was a 100% probability to be detected over a two-year period). Periodic screening was the most important component for the overall sensitivity in infected areas. In other areas, where periodic screening had stopped, tracing-on epidemiological investigation was the most sensitive component of the system. Screening exchanged animals had a negligible part in the overall sensitivity of the surveillance system.

Generative models of network dynamics provide insight into the effects of trade on endemic livestock disease

We develop and apply analytically tractable generative models of livestock movements at national scale. These go beyond current models through mechanistic modelling of heterogeneous trade partnership network dynamics and the trade events that occur on them. Linking resulting animal movements to disease transmission between farms yields analytical expressions for the basic reproduction number R ₀. We show how these novel modelling tools enable systems approaches to disease control, using R ₀ to explore impacts of changes in trading practices on between-farm prevalence levels. Using the Scottish cattle trade network as a case study, we show our approach captures critical complexities of real-world trade networks at the national scale for a broad range of endemic diseases. Changes in trading patterns that minimize disruption to business by maintaining in-flow of animals for each individual farm reduce R ₀, with the largest reductions for diseases that are most challenging to eradicate. Incentivizing high-risk farms to adopt such changes exploits 'scale-free' properties of the system and is likely to be particularly effective in reducing national livestock disease burden and incursion risk. Encouragingly, gains made by such targeted modification of trade practices scale much more favourably than comparably targeted improvements to more commonly adopted farm-level biosecurity.

Use of Network Analysis and Spread Models to Target Control Actions for Bovine Tuberculosis in a State from Brazil

Livestock movements create complex dynamic interactions among premises that can be represented, interpreted, and used for epidemiological purposes. These movements are a very important part of the production chain but may also contribute to the spread of infectious diseases through the transfer of infected animals over large distances. Social network analysis (SNA) can be used to characterize cattle trade patterns and to identify highly connected premises that may act as hubs in the movement network, which could be subjected to targeted control measures in order to reduce the transmission of communicable diseases such as bovine tuberculosis (TB). Here, we analyzed data on cattle movement and slaughterhouse surveillance for detection of TB-like lesions (TLL) over the 2016-2018 period in the state of Rio Grande do Sul (RS) in Brazil with the following aims: (i) to characterize cattle trade describing the static full, yearly, and monthly snapshots of the network contact trade, (ii) to identify clusters in the space and contact networks of premises from which animals with TLL originated, and (iii) to evaluate the potential of targeted control actions to decrease TB spread in the cattle population of RS using a stochastic metapopulation disease transmission model that simulated within-farm and between-farm disease spread. We found heterogeneous densities of premises and animals in the study area. The analysis of the contact network revealed a highly connected (~94%) trade network, with strong temporal trends, especially for May and November. The TLL cases were significantly clustered in space and in the contact network, suggesting the potential for both local (e.g., fence-to-fence) and movement-mediated TB transmission. According to the disease spread model, removing the top 7% connected farms based on degree and betweenness could reduce the total number of infected farms over three years by >50%. In conclusion, the characterization of the cattle network suggests that highly connected farms may play a role in TB dissemination, although being close to infected farms was also identified as a risk factor for having animals with TLL. Surveillance and control actions based on degree and betweenness could be useful to break the transmission cycle between premises in RS.

Quantifying intraherd cattle movement metrics: Implications for disease transmission risk

There are a paucity of data quantifying on-farm management practices such as the frequency of intraherd cattle movements, use of consolidated or spatially fragmented grazing pastures, and duration of time cattle spend at grass with respect to biosecurity and disease transmission. Such movement dynamics are important when attempting to understand the maintenance of chronic infectious disease, such as bovine tuberculosis (bTB). We captured empirical data on daily cattle movements for a sample of eighteen farms throughout one complete grazing season (n = 18,988 grazing days) and assessed these attributes in relation to herd bTB risk. Dairy herds were stocked at significantly higher densities compared to beef production systems (6.6 animals/ha, 95 % confidence intervals (CI) 6.5-6.7 and 4.1 animals/ha, 95 %CI 4.1 - 4.1 respectively, p < 0.001). Most notably milking cows, were grazed at higher densities than other life stages (e.g. calves, heifers and bullocks) (p < 0.001) and experienced four times the number of movements between pastures. Beef cattle were more likely to be grazed across multiple (rather than single) fields (p < 0.001), with greater time spent on fragmented land away from the main/home farm (p < 0.001). None of the farm or herd attributes analysed (e.g. stocking density, frequency of movement, movement distances or land fragmentation) were associated with herd bovine tuberculosis (bTB) breakdowns during this study. However, there was a weak positive association between bTB breakdowns during the 3 years prior to the study and cattle movement distances (p = 0.05) and time spent on fragmented land (p = 0.08). After a bTB breakdown occurs, restrictions on animals moving out of these herds are implemented to control disease spread, yet we argue that more attention is needed on the role of intraherd grazing patterns in modelling disease transmission risk between herds.

Characterization of potential superspreader farms for bovine tuberculosis: A review

Background

Variation in host attributes that influence their contact rates and infectiousness can lead some individuals to make disproportionate contributions to the spread of infections. Understanding the roles of such ‘superspreaders’ can be crucial in deciding where to direct disease surveillance and controls to greatest effect. In the epidemiology of bovine tuberculosis (bTB) in Great Britain, it has been suggested that a minority of cattle farms or herds might make disproportionate contributions to the spread of Mycobacterium bovis, and hence might be considered ‘superspreader farms’.

Objectives and Methods

We review the literature to identify the characteristics of farms that have the potential to contribute to exceptional values in the three main components of the farm reproductive number ‐ R_f: contact rate, infectiousness and duration of infectiousness, and therefore might characterize potential superspreader farms for bovine tuberculosis in Great Britain.

Results

Farms exhibit marked heterogeneity in contact rates arising from between‐farm trading of cattle. A minority of farms act as trading hubs that greatly augment connections within cattle trading networks. Herd infectiousness might be increased by high within‐herd transmission or the presence of supershedding individuals, or infectiousness might be prolonged due to undetected infections or by repeated local transmission, via wildlife or fomites.

Conclusions

Targeting control methods on putative superspreader farms might yield disproportionate benefits in controlling endemic bovine tuberculosis in Great Britain. However, real‐time identification of any such farms, and integration of controls with industry practices, present analytical, operational and policy challenges.

Mycobacterium bovis Population Structure in Cattle and Local Badgers: Co-Localisation and Variation by Farm Type

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.

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

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.

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.

Clustering and spatial heterogeneity of bovine tuberculosis at the livestock/wildlife interface areas in Namwala District of Zambia

BACKGROUND AND AIM

Bovine tuberculosis (bTB) remains a major public health issue in Zambia and has been exacerbated by human immunodeficiency virus prevalence and consumption of unpasteurized milk in the Southern Province of the country. The prevalence of bTB has been established to be linked to Kafue Lechwe, which act as reservoir hosts and share grazing fields with domestic cattle. No studies have so far used geographic information system (GIS) to investigate the relationship between the reservoir hosts (Kafue Lechwe) and domestic animals. This study, therefore, aimed to apply GIS to investigate the spatial distribution of bTB in Namwala District of the Southern Province of the country.

MATERIALS AND METHODS

To investigate the spatial distribution of bTB, geographical positioning system (GPS) coordinates representing 96 cattle herds across 20 independent villages were captured alongside risk factor data. The 96 herds were based on abattoir reports of condemned carcasses and a trace back. Positive herds were confirmed by cross-reference to purified protein derivative tests conducted by the District Veterinary Office. The GPS coordinates were transferred into ArcView 3.2 and laid on the map of Namwala District alongside physical features, including national parks, game management areas, and flood plains. Questionnaires were administered across 96 independent households to assess risk factors of bTB transmission.

RESULTS

The results revealed a "clustered" spatial distribution of the disease in cattle in Namwala District of Zambia, particularly significant in the eastern interface areas of the district (p=0.006 using Moran's I). Abattoir to production area trace back revealed a herd-level prevalence of 36.4% (95% CI=26.7-46.3%) among cattle herds in Namwala District, whereas individual animal prevalence ranged from 0% to 14% (95% CI=2.4-26.2%). Further, GPS data indicated that the majority of the positive herds were located at the livestock/wildlife interface area. Contacts with wildlife, coupled with sharing grazing, and watering points were found to be significant risk factors for bTB transmission.

CONCLUSION

This study demonstrated the presence of bTB in cattle and associated spatial risk factors. In particular, bTB was observed to be a function of animal location within the livestock/wildlife interface area. GIS is thus an applicable and important tool in studying disease distribution.

Cattle movements in Northern Ireland form a robust network: implications for disease management

The movements of undetected infected animals can facilitate long-distance pathogen spread, making control and eradication difficult by (re)infecting disease-free populations. Characterising movement patterns is essential in understanding pathogen spread and how potential interventions, particularly animal movement restrictions, could help as a control mechanism. In Northern Ireland (NI), cattle movements are important contributors to a significant portion of agricultural trade. They can be disrupted due to statutory interventions, for example, during bovine tuberculosis (bTB) control. Identifying populations at risk of becoming infected would allow for improved resource allocation. This could be through targeting herds with an above-average risk of becoming infected or spreading (amplifying) infection, and restricting their movement to manage future outbreaks. In this study, cattle movements were investigated using social network analysis (SNA) at the monthly temporal scale across NI during 2010-2015. Targeted and random herd restrictions were compared and their impact on the structure and connectivity of the networks' was assessed (e.g. connected component subgraphs). This work was contextualised in relation to bTB, the most persistent infectious disease currently impacting agriculture in NI, where reduced connectivity would represent potential reduced vulnerability from infection introduction. There was seasonal variation in network size and level of connectivity with spring and autumn being the largest and most connected due to common farming practices in NI. Across the study period, there was limited inter-annual variation in global network metrics. On average there were 6.28 movements between each pair of nodes each month, low reciprocity (mean of 0.155) and the networks were moderately accessible with an average path length of 4.28. Movements were not confined to within each disease management area but frequently occurred between these areas (mean assortativity of -0.0731) and herds with high degree interacted with herds of low degree (mean assortativity of -0.351). The Giant Weakly Connected Component (GWCC) spanned most of the networks (between 75% and 100% of nodes); however the Giant Strongly Connected Component (GSCC) included, at most, 23% of the network. There was heterogeneous contributions across NI with little participation in the GSCC from some disease management areas, and the GSCC was comprised predominantly of 'beef breeders', 'beef rearers', and 'other/mixed' type herds. Targeted restrictions were more effective at fragmenting the network than randomly restricting movements when 25% of nodes or more were removed. Cattle networks in NI are extremely interconnected and robust to movement restrictions, suggesting potential vulnerability to movement-facilitated pathogen spread, such as bTB.

Analysing livestock network data for infectious disease control: an argument for routine data collection in emerging economies

Livestock movements are an important mechanism of infectious disease transmission. Where these are well recorded, network analysis tools have been used to successfully identify system properties, highlight vulnerabilities to transmission, and inform targeted surveillance and control. Here we highlight the main uses of network properties in understanding livestock disease epidemiology and discuss statistical approaches to infer network characteristics from biased or fragmented datasets. We use a 'hurdle model' approach that predicts (i) the probability of movement and (ii) the number of livestock moved to generate synthetic 'complete' networks of movements between administrative wards, exploiting routinely collected government movement permit data from northern Tanzania. We demonstrate that this model captures a significant amount of the observed variation. Combining the cattle movement network with a spatial between-ward contact layer, we create a multiplex, over which we simulated the spread of 'fast' ( R0 = 3) and 'slow' ( R0 = 1.5) pathogens, and assess the effects of random versus targeted disease control interventions (vaccination and movement ban). The targeted interventions substantially outperform those randomly implemented for both fast and slow pathogens. Our findings provide motivation to encourage routine collection and centralization of movement data to construct representative networks. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.

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.

Burkholderia mallei: The dynamics of networks and disease transmission

Glanders is a highly infectious zoonotic disease caused by Burkholderia mallei. The transmission of B. mallei occurs mainly by direct contact, and horses are the natural reservoir. Therefore, the identification of infection sources within horse populations and animal movements is critical to enhance disease control. Here, we analysed the dynamics of horse movements from 2014 to 2016 using network analysis in order to understand the flow of animals in two hierarchical levels, municipalities and farms. The municipality-level network was used to investigate both community clustering and the balance between the municipality's trades and the farm-level network associations between B. mallei outbreaks and the network centrality measurements, analysed by spatio-temporal generalized additive model (GAM). Causal paths were established for the dispersion of B. mallei outbreaks through the network. Our approach captured and established a direct relationship between movement of infected equines and predicted B. mallei outbreaks. The GAM model revealed that the parameters in degree and closeness centrality out were positively associated with B. mallei. In addition, we also detected 10 communities with high commerce among municipalities. The role of each municipality within the network was detailed, and significant changes in the structures of the network were detected over the course of 3 years. The results suggested the necessity to focus on structural changes of the networks over time to better control glanders disease. The identification of farms with a putative risk of B. mallei infection using the horse movement network provided a direct opportunity for disease control through active surveillance, thus minimizing economic losses and risks for human cases of B. mallei.

The Distribution of Bovine Tuberculosis in Cattle Farms Is Linked to Cattle Trade and Badger-Mediated Contact Networks in South-Western France, 2007-2015

Bovine tuberculosis (bTB), mainly caused by Mycobacterium bovis, can affect domestic and wild animals as well as humans. Identifying the major transmission mechanisms in an area is necessary for disease control and management. In this study, we aimed to evaluate the involvement of different types of contact in M. bovis transmission between cattle farms of south-western France between 2007 and 2015. We analyzed an empirical contact network of cattle farms as nodes, with known infection status and molecular types (16 circulated during the study period of which 14 affected only cattle and two both badgers and cattle). Edges were based on cattle trade data (T-edges) and on spatial neighborhood relationships between farms, either direct (P-edges) or badger-mediated, when two farms neighbored the same badger home range (B-edges), or two distinct but neighboring badger home ranges (D-edges). Edge types were aggregated so that the contact network contained only unique edges labeled by one or several edge types. The association between the contact network structure and bTB infection status was assessed using a non-parametric test, each molecular type being considered a marker of an independent epidemic. Using a logistic regression model, we estimated the contribution of each edge type to the probability for an edge originating from an infected farm to end at another infected farm. A total number of 1946 cattle farms were included in the study and were linked by 54,243 edges. Within this contact network, infected farms (whatever the molecular type) always belonged to the same component, suggesting the contact network may have supported bTB spread among those farms. A significant association between the pattern of bTB-infected farms and the structure of the contact network was observed when all the molecular types were simultaneously considered. The logistic regression model showed a significant association between M. bovis infection in direct neighbors of infected farms and the connection by T-, B- and D-edges, with odds-ratios of 7.4, 1.9, and 10.4, respectively. These results indicate a multifactorial M. bovis transmission between cattle farms of the studied area, with varying implication levels of the trade, pasture and badger networks according to the molecular type.

Optimal surveillance strategies for bovine tuberculosis in a low-prevalence country

Bovine tuberculosis (bTB) is a chronic disease of cattle that is difficult to control and eradicate in part due to the costly nature of surveillance and poor sensitivity of diagnostic tests. Like many countries, bTB prevalence in Uruguay has gradually declined to low levels due to intensive surveillance and control efforts over the past decades. In low prevalence settings, broad-based surveillance strategies based on routine testing may not be the most cost-effective way for controlling between-farm bTB transmission, while targeted surveillance aimed at high-risk farms may be more efficient for this purpose. To investigate the efficacy of targeted surveillance, we developed an integrated within- and between-farm bTB transmission model utilizing data from Uruguay's comprehensive animal movement database. A genetic algorithm was used to fit uncertain parameter values, such as the animal-level sensitivity of skin testing and slaughter inspection, to observed bTB epidemiological data. Of ten alternative surveillance strategies evaluated, a strategy based on eliminating testing in low-risk farms resulted in a 40% reduction in sampling effort without increasing bTB incidence. These results can inform the design of more cost-effective surveillance programs to detect and control bTB in Uruguay and other countries with low bTB prevalence.

Investigation of intra-herd spread of Mycobacterium caprae in cattle by generation and use of a whole-genome sequence

Single nucleotide polymorphisms (SNPs) calculated from whole genome sequencing (WGS) are ideally suited to study evolutionary relationships of pathogens and their epidemiology. Mycobacterium caprae infections have been documented frequently in cattle and red deer along the Bavarian and Austrian Alps during the last decade. However, little is still known about the transmission within cattle holdings and possible alterations of the genomes of M. caprae during such events. The aim of this study was to study the molecular epidemiology of bovine tuberculosis (bTB) in selected herds based on isolate-specific genome-wide SNPs and to perform a phylogenetic network analysis. In total, 61 M. caprae isolates were collected originating from eight cattle farms over a period of twelve years between 2004 and 2015. Analysis of their sequence data revealed that the M. caprae isolates of an affected farm differ at all in a few SNPs. In contrast, many more SNPs were found when comparing the M. caprae genomes originating from different herds. The results demonstrated that the spread of bTB in the affected farms occurred by direct transmission between the members of each herd rather than between herds and a M. caprae introduction in farms after contact events e. g. on summer pastures can readily be traced by WGS analysis. Furthermore, we assembled a nearly complete whole genome sequence of M. caprae derived from several cattle isolates originating from bTB cases in the Bavarian Alpine region.

Analysis of the Spatial Organization of Pastures as a Contact Network, Implications for Potential Disease Spread and Biosecurity in Livestock, France, 2010

The use of pastures is part of common herd management practices for livestock animals, but contagion between animals located on neighbouring pastures is one of the major modes of infectious disease transmission between herds. At the population level, this transmission is strongly constrained by the spatial organization of pastures. The aim of this study was to answer two questions: (i) is the spatial configuration of pastures favourable to the spread of infectious diseases in France? (ii) would biosecurity measures allow decreasing this vulnerability? Based on GIS data, the spatial organization of pastures was represented using networks. Nodes were the 3,159,787 pastures reported in 2010 by the French breeders to claim the Common Agricultural Policy subsidies. Links connected pastures when the distance between them was below a predefined threshold. Premises networks were obtained by aggregating into a single node all the pastures under the same ownership. Although the pastures network was very fragmented when the distance threshold was short (1.5 meters, relevant for a directly-transmitted disease), it was not the case when the distance threshold was larger (500 m, relevant for a vector-borne disease: 97% of the nodes in the largest connected component). The premises network was highly connected as the largest connected component always included more than 83% of the nodes, whatever the distance threshold. Percolation analyses were performed to model the population-level efficacy of biosecurity measures. Percolation thresholds varied according to the modelled biosecurity measures and to the distance threshold. They were globally high (e.g. >17% of nodes had to be removed, mimicking the confinement of animals inside farm buildings, to obtain the disappearance of the large connected component). The network of pastures thus appeared vulnerable to the spread of diseases in France. Only a large acceptance of biosecurity measures by breeders would allow reducing this structural risk.