Impact of changes in cattle movement regulations on the risks of bovine tuberculosis for Scottish farms

Is badger culling associated with risk compensation behaviour among cattle farmers?

BACKGROUND

Risk compensation theory suggests that behaviours are modified in response to interventions that remove risks by substituting them with other risky behaviours to maintain a 'risk equilibrium'. Alternatively, risk reduction interventions may result in spill-over behaviours that seek to minimise risks further. This paper assessed evidence for these behavioural risk responses among farmers in response to badger culling that seeks to remove the risk of bovine tuberculosis in cattle.

METHODS

Data from the UK's randomised badger culling trial were re-analysed, comparing farmers' cattle movement practices in proactive and reactive culling areas and control areas. Analysis compared cattle movements during and after the trial using zero-inflated negative binomial regression.

RESULTS

The analysis found no strong evidence of risk compensation behaviours among farmers who experienced proactive culling. However, strong evidence for a reduction in cattle movements in reactive culling areas was found. The results indicate high levels of inertia within farming systems in relation to cattle purchasing.

LIMITATIONS

Data do not account for the risk of cattle purchases and reflect previous policy regimens. Evidence from recent badger culling interventions should be analysed.

CONCLUSION

Proactive badger culling was not associated with risk compensation behaviours, while reactive badger culling was associated with decreased risk taking among farmers.

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.

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.

Is there an association between road building and bovine tuberculosis herd risk? A three time-point study in Ireland, 2011-2019

Bovine tuberculosis (bTB) is a chronic infectious disease caused by Mycobacterium bovis which results in a significant economic cost to cattle industries and governments where it is endemic. In Ireland, the European badger is the main wildlife reservoir of infection. In this study, we investigated whether (motorway) road construction was associated with an increased risk of bTB in associated cattle herds. For this study, we considered three observation periods: pre-construction (2011-2014), construction (2015-2017) and post-construction (2018-2019). We selected 1543 herds situated, based on proximity, between >50 m and <5 km of the roadworks, and extracted information about their herd-size, herd-type, inward animal movements, bTB history, and distance to the roadworks. Generalized linear mixed models were performed, whose outcome were whether a herd experienced a bTB breakdown with ≥1 or ≥3 standard reactor/s, respectively. Herds located at a distance of >3 km from the roadworks were found to be at reduced risk of a bTB breakdown over the construction period compared with those situated within 1 km of the roadworks for ≥1 reactor/s (>3 km and construction vs. <1 km: OR: 0.595, 95 % Confidence Interval (CI): 0.354-0.999) or ≥3 reactors (>3 km and construction vs. <1 km: OR: 0.431, 95 % CI: 0.174-1.067). Other previously reported risk factors such as inward movements, herd-size and herd-type were also associated with bTB risk in the final models (≥1 reactor/s and ≥3 reactors). These findings appear to be consistent with bTB breakdowns being a consequence as opposed to coincident to road construction, given the temporal and spatial consistency of the evidence. The potential for badger social group disturbance leading to the spatial spread of infection to cattle herds, as previously described in the United Kingdom, could be a hypothetical mechanism to explain these findings. However, our findings are not consistent with previous Irish studies, including recent work from another road construction project, albeit running alongside and cross over an existing road rather than construction of a new road as in this case, or experiences from national targeted badger removal. Further research is warranted to verify this pattern occurs elsewhere, and the underlying biological mechanism. Until further data are available, we recommend that badgers are vaccinated, as a precautionary measure, in advance of the commencement of major roadworks.

Rewiring cattle trade movements helps to control bovine paratuberculosis at a regional scale

Paratuberculosis is a worldwide disease mainly introduced through trade. Due to the low sensitivity of diagnostic tests, it is difficult to protect herds from purchasing infected animals. Our objective was to assess if rewiring trade networks to promote risk-based movements could reduce the spread of Mycobacterium avium subsp. paratuberculosis (MAP) between dairy cattle herds at a regional scale. Two levels of control strategies were assessed. At the between-herd scale, trade rewiring aimed to prevent animals from high-risk herds moving into low-risk herds. At the within-herd scale, complementary additional measures were considered based on the herd infection status, aiming to limit the within-herd spread by reducing calf exposure to adult faeces and culling more rapidly after positive test results. We used a stochastic individual-based and between-herd mechanistic epidemiological model adapted to the 12,857 dairy cattle herds located in Brittany, western France. We compared the regional spread of MAP using observed trade movements against a rewiring algorithm rendering trade movements risk-based. All females over two years old were tested. Based on the results, and taking into account the low test sensitivity, herds were annually assigned one of three statuses: A if the estimated true prevalence was below 7%, B if it ranged from 7 to 21 %, C otherwise. We also identified herds with a high probability of being MAP-free (AAA herds that had obtained an A status over three consecutive years) to assess the effect of decreasing their risk of purchasing infected animals on MAP regional spread. We showed that movement rewiring to prevent the sale of animals from high to low-prevalence herds reduces MAP regional spread. Targeting AAA herds made it possible to minimize the control effort to decrease MAP regional spread. However, animals purchased by AAA herds should have a moderate to high probability of being MAP-free, especially if the risk of purchasing animals from herds of unknown status cannot be managed. Improved hygiene and early culling of positive animals were relevant complementary on-farm control options to further decrease MAP spread. Future studies should identify how to define herd statuses to target optimal control measure combinations that could reduce the spread of MAP on a regional scale most effectively.

Using machine learning improves predictions of herd-level bovine tuberculosis breakdowns in Great Britain

In the United Kingdom, despite decades of control efforts, bovine tuberculosis (bTB) has not been controlled and currently costs ~ £100 m annually. Critical in the failure of control efforts has been the lack of a sufficiently sensitive diagnostic test. Here we use machine learning (ML) to predict herd-level bTB breakdowns in Great Britain (GB) with the aim of improving herd-level diagnostic sensitivity. The results of routinely-collected herd-level tests were correlated with risk factor data. Four ML methods were independently trained with data from 2012–2014 including ~ 4700 positive herd-level test results annually. The best model’s performance was compared to the observed sensitivity and specificity of the herd-level test calculated on the 2015 data resulting in an increased herd-level sensitivity from 61.3 to 67.6% (95% confidence interval (CI): 66.4–68.8%) and herd-level specificity from 90.5 to 92.3% (95% CI: 91.6–93.1%). This approach can improve predictive capability for herd-level bTB and support disease control.

Challenges and opportunities for using national animal datasets to support foot-and-mouth disease control

National level databases of animal numbers, locations and movements provide the essential foundations for disease preparedness, outbreak investigations and control activities. These activities are particularly important for managing and mitigating the risks of high-impact transboundary animal disease outbreaks such as foot-and-mouth disease (FMD), which can significantly affect international trade access and domestic food security. In countries where livestock production systems are heavily subsidized by the government, producers are often required to provide detailed animal movement and demographic data as a condition of business. In the remaining countries, it can be difficult to maintain these types of databases and impossible to estimate the extent of missing or inaccurate information due to the absence of gold standard datasets for comparison. Consequently, competent authorities are often required to make decisions about disease preparedness and control based on available data, which may result in suboptimal outcomes for their livestock industries. It is important to understand the limitations of poor data quality as well as the range of methods that have been developed to compensate in both disease-free and endemic situations. Using FMD as a case example, this review first discusses the different activities that competent authorities use farm-level animal population data for to support (1) preparedness activities in disease-free countries, (2) response activities during an acute outbreak in a disease-free country, and (3) eradication and control activities in an endemic country. We then discuss (4) data requirements needed to support epidemiological investigations, surveillance, and disease spread modelling both in disease-free and endemic countries.

The Use of Sheep Movement Data to Inform Design and Interpretation of Slaughterhouse-Based Surveillance Activities

The design of surveillance strategies is often a compromise between science, feasibility, and available resources, especially when sampling is based at fixed locations, such as slaughter-houses. Advances in animal identification, movement recording and traceability should provide data that can facilitate the development, design and interpretation of surveillance activities. Here, for the first time since the introduction of electronic identification of sheep, the utility of a statutory sheep movement database to inform the design and interpretation of slaughter-house based surveillance activities has been investigated. Scottish sheep movement records for 2015–2018 were analyzed in combination with several other data sources. Patterns of off-farm movements of Scottish sheep to slaughter were described and the spatial distribution of several distinct slaughter populations, throughputs and catchment areas for Scottish slaughterhouses were determined. These were used to evaluate the coverage of a convenience-sample slaughter-house based survey for antimicrobial resistance (AMR). In addition, non-slaughter sheep movements within and between Scottish regions were described and inter-and intra-regional movement matrices were produced. There is potential at a number of levels for bias in spatially-associated factors for ovine surveillance activities based at Scottish slaughterhouses. The first is intrinsic because the slaughtered in Scotland population differs from the overall Scottish sheep slaughter population. Other levels will be survey-dependent and occur when the catchment area differs from the slaughtered in Scotland population and when the sampled sheep differ from the catchment area. These are both observed in the AMR survey. Furthermore, the Scottish non-slaughter sheep population is dynamic. Inter-regional movements vary seasonally, driven by the sheep calendar year, structure of the Scottish sheep industry and management practices. These sheep movement data provide a valuable resource for surveillance purposes, despite a number of challenges and limitations that were encountered. They can be used to identify and characterize the spatial origin of relevant populations and so inform the interpretation of existing slaughterhouse-based surveillance activities. They can be used to improve future design by exploring the feasibility and cost:benefit of alternative sampling strategies. Further development could also contribute to other surveillance activities, such as situational awareness and resource allocation, for the benefit of stakeholders.

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.

Resilience of French cattle farms to bovine tuberculosis detection between 2004 and 2017

France was recognized officially bovine tuberculosis (bTB) free by the European Union in 2001, however an increase of bTB detections has been reported since 2004. Even though the recommended method for bTB control is whole herd depopulation, test-and-cull protocols have been authorized in pilot areas since 2008 and in the rest of France since 2014. BTB impact at the state level and on trade has been thoroughly studied, however the consequences of these control measures at a farm level are poorly understood. We used bovine movement data from the French cattle tracing system and surveillance data from the National reference laboratory to compare time to closure between case farms with a bTB detection and matched control farms between 2004 and 2017 in France. For this purpose, we considered two modes of closure: (i) long-lasting (more than 12 months) depopulation and (ii) change of farm owner. Using a competing risk analysis, we showed that bTB detection significantly increased the odds of long-lasting depopulation (particularly during the first three months after bTB detection) indicating that farmers renounced restocking after the depopulation, whereas it decreased the odds of a change of owner. Larger farms, characterized by an increased average weekly number of cattle, had a lesser risk of long-lasting depopulation. Farms owned by a natural person had an increased risk of closure. We also showed that the possibility to control bTB by test-and-cull protocol decreased the long-lasting depopulation risk. Overall, bTB control measures contribute to reshaping the agricultural landscape by increasing the probability of closure for small vulnerable farms and by favoring large, professionalized and specialized agricultural holdings. Our results also suggest an improvement in control management with the introduction of test-and-cull protocols instead of systematic whole herd depopulation.

Descriptive analysis of horse movement networks during the 2015 equestrian season in Ontario, Canada

Horses are a highly mobile population, with many travelling locally, nationally, and internationally to participate in shows and sporting events. However, the nature and extent of these movements, as well as the potential impact they may have on disease introduction and spread, is not well documented. The objective of this study was to characterise the movement network of a sample of horses in Ontario, Canada, over a 7-month equestrian season. Horse owners (n = 141) documented their travel patterns with their horse(s) (n = 330) by completing monthly online questionnaires between May and November 2015. Directed networks were constructed to represent horse movements in 1-month time periods. A total of 1754 horse movements met the inclusion criteria for analysis. A variety of location types were included in each monthly network, with many including non-facilities such as parks, trails, and private farms. Only 34.3% of competitions attended by participants during the study period were regulated by an official equestrian organisation. Comparisons of the similarity between monthly networks indicated that participants did not travel to the same locations each month, and the most connected locations varied between consecutive months. While the findings should not be generalized to the wider horse population, they have provided greater insight into the nature and extent of observed horse movement patterns. The results support the need to better understand the variety of locations to which horses can travel in Ontario, as different types of locations may have different associated risks of disease introduction and spread.

Why sold, not culled? Analysing farm and animal characteristics associated with livestock selling practices

Livestock disease simulation models that incorporate animal movements often assume (1) that farmers' livestock trading practices remain consistent over time in future, (2) that animals sold to other farms are chosen randomly from a herd, and (3) that the animals' fate on the destination farm is not influenced by their past production and movement histories. The objective of this study was to assess the extent to which these assumptions are violated in the real world using records from a national database in New Zealand that captures both milk production and movement data for individual dairy cattle. All individual animal milk test records from 2006 through 2010 were extracted from the database and processed to generate different animal and herd level variables including cow demographics, previous movement history, milk volume, and milk composition (somatic cell counts (SCC), protein percentage, and fat percentage). Various statistical models were used to explore factors associated with farms' selling practice and characteristics of animals being sold. The results showed farms' livestock selling practices were highly influenced by both external factors such as market milk price and internal factors such as previous year's cow mortality and how long farms had been in business. Higher milk price increased both the number of cows being sold and the number of farms selling cows. Compared with cows that remained in the herd at the end of lactation, cows sold to other farms had lower fat and protein percentages, but similar milk volumes and SCCs. Cows that had been sold more often in the past were more likely to be sold after controlling for the effects of age. Overall, these findings highlight the potential need for disease simulation models to account for dynamics in selling practices and animal characteristics when determining which animals will be sold to other herds.

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.

Epidemics on dynamic networks

In many populations, the patterns of potentially infectious contacts are transients that can be described as a network with dynamic links. The relative timescales of link and contagion dynamics and the characteristics that drive their tempos can lead to important differences to the static case. Here, we propose some essential nomenclature for their analysis, and then review the relevant literature. We describe recent advances in they apply to infection processes, considering all of the methods used to record, measure and analyse them, and their implications for disease transmission. Finally, we outline some key challenges and opportunities in the field.

Biosecurity practices in Belgian cattle farming: Level of implementation, constraints and weaknesses

Over the last few years, a shift from curative towards preventive medicine occurred in the livestock sector. This led to an increased importance of biosecurity to better control infectious diseases by preventing their introduction and/or reducing their spread. Farmers are the main responsible actors of biosecurity measures (BSM). Existing studies report a low implementation level of BSM by the cattle farmers. Barriers such as cost, usefulness, importance, workload and lack of knowledge were investigated but the decision-making process of farmers related to a given BSM is not yet clarified. The objectives of this study were to (i) assess the level of implementation of BSM in cattle farms, (ii) assess the correlation between the importance that farmers give to a BSM and its effective implementation and (iii) identify the main reasons of non-implementation. A randomized survey was implemented in Belgium from December 2016 up to April 2017 with face-to-face interviews conducted in 100 Belgian farms. A descriptive analysis of data was performed using Microsoft Excel^® and Stata14^® . Chi-square and Spearman's rank correlation tests, respectively, allowed comparing implementation levels in dairy herds vs. beef herds and investigating the correlation between the importance that farmers give to a BSM and its implementation level. Biosecurity measures were poorly implemented to prevent disease introduction through direct contact and almost not to avoid indirect transmission. Some measures showed a significant difference in terms of implementation level between beef and dairy herds. A positive correlation was highlighted between the importance that farmers give to a BSM and its actual effective implementation. Perceived lack of efficiency, feasibility and usefulness are the reasons most often mentioned for non-implementation. Other factors potentially influencing the decision-making process should be further investigated and clarified. Evidence-based studies would be useful to convince the farmers of the need of implementing BSM.

Theoretical value of pre-trade testing for Salmonella in Swedish cattle herds

The Swedish Salmonella control programme includes mandatory action if Salmonella is detected in a herd. The aim of this study was to assess the relative value of different strategies for pre-movement testing of cattle. Three fictitious herds were included: dairy, beef and specialised calf-fattening. The yearly risks of introducing Salmonella with and without individual serological or bulk milk testing were assessed as well as the effects of sourcing animals from low-prevalence areas or reducing the number of source herds. The initial risk was highest for the calf-fattening herd and lowest for the beef herd. For the beef and dairy herds, the yearly risk of Salmonella introduction was reduced by about 75% with individual testing. Sourcing animals from low-prevalence areas reduced the risk by >99%. For the calf-fattening herd, the yearly risk was reduced by almost 50% by individual testing or sourcing animals from a maximum of five herds. The method was useful for illustrating effects of risk mitigation when introducing animals into a herd. Sourcing animals from low-risk areas (or herds) is more effective than single testing of individual animals or bulk milk. A comprehensive approach to reduce the risk of introducing Salmonella from source herds is justified.

Genomic regions underlying susceptibility to bovine tuberculosis in Holstein-Friesian cattle

BACKGROUND

The significant social and economic loss as a result of bovine tuberculosis (bTB) presents a continuous challenge to cattle industries in the UK and worldwide. However, host genetic variation in cattle susceptibility to bTB provides an opportunity to select for resistant animals and further understand the genetic mechanisms underlying disease dynamics.

METHODS

The present study identified genomic regions associated with susceptibility to bTB using genome-wide association (GWA), regional heritability mapping (RHM) and chromosome association approaches. Phenotypes comprised de-regressed estimated breeding values of 804 Holstein-Friesian sires and pertained to three bTB indicator traits: i) positive reactors to the skin test with positive post-mortem examination results (phenotype 1); ii) positive reactors to the skin test regardless of post-mortem examination results (phenotype 2) and iii) as in (ii) plus non-reactors and inconclusive reactors to the skin tests with positive post-mortem examination results (phenotype 3). Genotypes based on the 50 K SNP DNA array were available and a total of 34,874 SNPs remained per animal after quality control.

RESULTS

The estimated polygenic heritability for susceptibility to bTB was 0.26, 0.37 and 0.34 for phenotypes 1, 2 and 3, respectively. GWA analysis identified a putative SNP on Bos taurus autosomes (BTA) 2 associated with phenotype 1, and another on BTA 23 associated with phenotype 2. Genomic regions encompassing these SNPs were found to harbour potentially relevant annotated genes. RHM confirmed the effect of these genomic regions and identified new regions on BTA 18 for phenotype 1 and BTA 3 for phenotypes 2 and 3. Heritabilities of the genomic regions ranged between 0.05 and 0.08 across the three phenotypes. Chromosome association analysis indicated a major role of BTA 23 on susceptibility to bTB.

CONCLUSION

Genomic regions and candidate genes identified in the present study provide an opportunity to further understand pathways critical to cattle susceptibility to bTB and enhance genetic improvement programmes aiming at controlling and eradicating the disease.

Assessing the impact of a cattle risk-based trading scheme on the movement of bovine tuberculosis infected animals in England and Wales

The adoption of bovine tuberculosis (bTB) risk-based trading (RBT) schemes has the potential to reduce the risk of bTB spread. However, any scheme will have cost implications that need to be balanced against its likely success in reducing bTB. This paper describes the first stochastic quantitative model assessing the impact of the implementation of a cattle risk-based trading scheme to inform policy makers and contribute to cost-benefit analyses. A risk assessment for England and Wales was developed to estimate the number of infected cattle traded using historic movement data recorded between July 2010 and June 2011. Three scenarios were implemented: cattle traded with no RBT scheme in place, voluntary provision of the score and a compulsory, statutory scheme applying a bTB risk score to each farm. For each scenario, changes in trade were estimated due to provision of the risk score to potential purchasers. An estimated mean of 3981 bTB infected animals were sold to purchasers with no RBT scheme in place in one year, with 90% confidence the true value was between 2775 and 5288. This result is dependent on the estimated between herd prevalence used in the risk assessment which is uncertain. With the voluntary provision of the risk score by farmers, on average, 17% of movements was affected (purchaser did not wish to buy once the risk score was available), with a reduction of 23% in infected animals being purchased initially. The compulsory provision of the risk score in a statutory scheme resulted in an estimated mean change to 26% of movements, with a reduction of 37% in infected animals being purchased initially, increasing to a 53% reduction in infected movements from higher risk sellers (score 4 and 5). The estimated mean reduction in infected animals being purchased could be improved to 45% given a 10% reduction in risky purchase behaviour by farmers which may be achieved through education programmes, or to an estimated mean of 49% if a rule was implemented preventing farmers from the purchase of animals of higher risk than their own herd. Given voluntary trials currently taking place of a trading scheme, recommendations for future work include the monitoring of initial uptake and changes in the purchase patterns of farmers. Such data could be used to update the risk assessment to reduce uncertainty associated with model estimates.

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.

Integrating novel data streams to support biosurveillance in commercial livestock production systems in developed countries: challenges and opportunities

Reducing the burden of emerging and endemic infectious diseases on commercial livestock production systems will require the development of innovative technology platforms that enable information from diverse animal health resources to be collected, analyzed, and communicated in near real-time. In this paper, we review recent initiatives to leverage data routinely observed by farmers, production managers, veterinary practitioners, diagnostic laboratories, regulatory officials, and slaughterhouse inspectors for disease surveillance purposes. The most commonly identified challenges were (1) the lack of standardized systems for recording essential data elements within and between surveillance data streams, (2) the additional time required to collect data elements that are not routinely recorded by participants, (3) the concern over the sharing and use of business sensitive information with regulatory authorities and other data analysts, (4) the difficulty in developing sustainable incentives to maintain long-term program participation, and (5) the limitations in current methods for analyzing and reporting animal health information in a manner that facilitates actionable response. With the significant recent advances in information science, there are many opportunities to develop more sophisticated systems that meet national disease surveillance objectives, while still providing participants with valuable tools and feedback to manage routine animal health concerns.

Milk yield and reproductive performance of Holstein cows testing positive for bovine tuberculosis

The objective of this study was to determine if high milk-yielding Holstein cows testing positive for bovine tuberculosis (bTB) are affected in their reproductive performance and milk yield. For this purpose, 1044 healthy cows and 105 bTB reactor cows were used. Tuberculosis reactor cows were from four large commercial dairy operations from the same region which were transferred from their barns to an isolated dairy facility. Cows free from this disease were placed in the same barn as the bTB reactor cows but in an isolated division and served as control animals. The analysis of variance with a general linear model for binary data showed that the reproductive performance of bTB reactors was impaired; overall pregnancy per artificial insemination differed (P < 0.05) between bTB reactor and non-reactor cows (16.9 vs. 20.7%). Cows that were TB reactors required 4.7 ± 2.9 services per pregnancy compared with 4.3 ± 2.8 for control cows (P > 0.05). The intervals between calving and conception were similar between bTB reactors (154 ± 78 days) and control animals (150 ± 80 days). Control cows tended (P = 0.08) to produce more milk than bTB reactors over a 305-day lactation (10,684 ± 1720 vs. 10,345 ± 1736; mean ± SD). Serum metabolites indicative of nutritional stress did not differ between bTB reactor and non-reactor cows. It was concluded that both reproductive performance and milk yield decreased marginally in bTB reactor cows, which explains the reluctance of milk producers to get rid of these animals.

Controlling infectious disease through the targeted manipulation of contact network structure

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation.

Eight challenges in modelling infectious livestock diseases

The transmission of infectious diseases of livestock does not differ in principle from disease transmission in any other animals, apart from that the aim of control is ultimately economic, with the influence of social, political and welfare constraints often poorly defined. Modelling of livestock diseases suffers simultaneously from a wealth and a lack of data. On the one hand, the ability to conduct transmission experiments, detailed within-host studies and track individual animals between geocoded locations make livestock diseases a particularly rich potential source of realistic data for illuminating biological mechanisms of transmission and conducting explicit analyses of contact networks. On the other hand, scarcity of funding, as compared to human diseases, often results in incomplete and partial data for many livestock diseases and regions of the world. In this overview of challenges in livestock disease modelling, we highlight eight areas unique to livestock that, if addressed, would mark major progress in the area.

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

Background

Bovine tuberculosis (bTB) remains difficult to eradicate from low incidence regions partly due to the imperfect sensitivity and specificity of routine intradermal tuberculin testing. Herds with unconfirmed reactors that are incorrectly classified as bTB-negative may be at risk of spreading disease, while those that are incorrectly classified as bTB-positive may be subject to costly disease eradication measures. This analysis used data from Scotland in the period leading to Officially Tuberculosis Free recognition (1) to investigate the risks associated with the movements of cattle from herds with different bTB risk classifications and (2) to identify herd demographic characteristics that may aid in the interpretation of tuberculin testing results.

Results

From 2002 to 2009, for every herd with confirmed bTB positive cattle identified through routine herd testing, there was an average of 2.8 herds with at least one unconfirmed positive reactor and 18.9 herds with unconfirmed inconclusive reactors. Approximately 75% of confirmed bTB positive herds were detected through cattle with no known movements outside Scotland. At the animal level, cattle that were purchased from Scottish herds with unconfirmed positive reactors and a recent history importing cattle from endemic bTB regions were significantly more likely to react positively on routine intradermal tuberculin tests, while cattle purchased from Scottish herds with unconfirmed inconclusive reactors were significantly more likely to react inconclusively. Case-case comparisons revealed few demographic differences between herds with confirmed positive, unconfirmed positive, and unconfirmed inconclusive reactors, which highlights the difficulty in determining the true disease status of herds with unconfirmed tuberculin reactors. Overall, the risk of identifying reactors through routine surveillance decreased significantly over time, which may be partly attributable to changes in movement testing regulations and the volume of cattle imported from endemic regions.

Conclusions

Although the most likely source of bTB infections in Scotland was cattle previously imported from endemic regions, we found indirect evidence of transmission within Scottish cattle farms and cannot rule out the possibility of low level transmission between farms. Further investigation is needed to determine whether targeting herds with unconfirmed reactors and a history of importing cattle from high risk regions would benefit control efforts.

The contribution of badgers to confirmed tuberculosis in cattle in high-incidence areas in England

The role of badgers in the transmission and maintenance of bovine tuberculosis (TB) in British cattle is widely debated as part of the wider discussions on whether badger culling and/or badger vaccination should play a role in the government’s strategy to eradicate cattle TB. The key source of information on the contribution from badgers within high-cattle-TB-incidence areas of England is the Randomised Badger Culling Trial (RBCT), with two analyses providing estimates of the average overall contribution of badgers to confirmed cattle TB in these areas. A dynamical model characterizing the association between the estimated prevalence of Mycobacterium bovis (the causative agent of bovine TB) among badgers culled in the initial RBCT proactive culls and the incidence among sympatric cattle herds prior to culling is used to estimate the average overall contribution of badgers to confirmed TB herd breakdowns among proactively culled areas. The resulting estimate based on all data (52%) has considerable uncertainty (bootstrap 95% confidence interval (CI): 9.1-100%). Separate analyses of experimental data indicated that the largest estimated reduction in confirmed cattle TB achieved inside the proactive culling areas was 54% (overdispersion-adjusted 95% CI: 38-66%), providing a lower bound for the average overall contribution of badgers to confirmed cattle TB. Thus, taking into account both results, the best estimate of the average overall contribution of badgers is roughly half, with 38% being a robustly estimated lower bound. However, the dynamical model also suggested that only 5.7% (bootstrap 95% CI: 0.9-25%) of the transmission to cattle herds is badger-to-cattle with the remainder of the average overall contribution from badgers being in the form of onward cattle-to-cattle transmission. These estimates, confirming that badgers do play a role in bovine TB transmission, inform debate even if they do not point to a single way forward.

Minimization of bovine tuberculosis control costs in US dairy herds

The objective of this study was to minimize the cost of controlling an isolated bovine tuberculosis (bTB) outbreak in a US dairy herd, using a stochastic simulation model of bTB with economic and biological layers. A model optimizer produced a control program that required 2-month testing intervals (TI) with 2 negative whole-herd tests to leave quarantine. This control program minimized both farm and government costs. In all cases, test-and-removal costs were lower than depopulation costs, although the variability in costs increased for farms with high holding costs or small herd sizes. Increasing herd size significantly increased costs for both the farm and the government, while increasing indemnity payments significantly decreased farm costs and increasing testing costs significantly increased government costs. Based on the results of this model, we recommend 2-month testing intervals for herds after an outbreak of bovine tuberculosis, with 2 negative whole herd tests being sufficient to lift quarantine. A prolonged test and cull program may cause a state to lose its bTB-free status during the testing period. When the cost of losing the bTB-free status is greater than $1.4 million then depopulation of farms could be preferred over a test and cull program.