Characteristics of cattle movements in Britain – an analysis of records from the Cattle Tracing System

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.

Modeling nation-wide U.S. swine movement networks at the resolution of the individual premises

The spread of infectious livestock diseases is a major cause for concern in modern agricultural systems. In the dynamics of the transmission of such diseases, movements of livestock between herds play an important role. When constructing mathematical models used for activities such as forecasting epidemic development, evaluating mitigation strategies, or determining important targets for disease surveillance, including between-premises shipments is often a necessity. In the United States (U.S.), livestock shipment data is not routinely collected, and when it is, it is not readily available and mostly concerned with between-state shipments. To bridge this gap in knowledge and provide insight into the complete livestock shipment network structure, we have developed the U.S. Animal Movement Model (USAMM). Previously, USAMM has only existed for cattle shipments, but here we present a version for domestic swine. This new version of USAMM consists of a Bayesian model fit to premises demography, county-level livestock industry variables, and two limited data sets of between-state swine movements. The model scales up the data to simulate nation-wide networks of both within- and between-state shipments at the level of individual premises. Here we describe this shipment model in detail and subsequently explore its usefulness with a rudimentary predictive model of the prevalence of porcine epidemic diarrhea virus (PEDv) across the U.S. Additionally, in order to promote further research on livestock disease and other topics involving the movements of swine in the U.S., we also make 250 synthetic premises-level swine shipment networks with complete coverage of the entire conterminous U.S. freely available to the research community as a useful surrogate for the absent shipment data.

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.

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.

The value of infectious disease modeling and trend assessment: a public health perspective

INTRODUCTION

Disease outbreaks of acquired immunodeficiency syndrome, severe acute respiratory syndrome, pandemic H1N1, H7N9, H5N1, Ebola, Zika, Middle East respiratory syndrome, and recently COVID-19 have raised the attention of the public over the past half-century. Revealing the characteristics and epidemic trends are important parts of disease control. The biological scenarios including transmission characteristics can be constructed and translated into mathematical models, which can help to predict and gain a deeper understanding of diseases.

AREAS COVERED

This review discusses the models for infectious diseases and highlights their values in the field of public health. This information will be of interest to mathematicians and clinicians, and make a significant contribution toward the development of more specific and effective models. Literature searches were performed using the online database of PubMed (inception to August 2020).

EXPERT OPINION

Modeling could contribute to infectious disease control by means of predicting the scales of disease epidemics, indicating the characteristics of disease transmission, evaluating the effectiveness of interventions or policies, and warning or forecasting during the pre-outbreak of diseases. With the development of theories and the ability of calculations, infectious disease modeling would play a much more important role in disease prevention and control of public health.

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

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

Contact chains of cattle farms in Great Britain

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

Comparative study in the control of bovine viral diarrhea

Bovine viral diarrhea virus (BVDV) is an important infectious agent affecting herd productivity and reproduction, and leading to massive economic losses. As such, BVD is the subject of a number of control and eradication schemes globally. The key elements of such schemes are: diagnosis and removal of persistently infected animals from herds; implementation of biosecurity practices aimed at preventing the introduction or re-introduction of BVDV in free herds; and ongoing surveillance to monitor the progress of the program and to detect new infections. The objective of this review is to examine the impact of BVD and the management of the disease in three countries: Scotland, Spain, and Argentina, where BVD control programs are in distinct phases: established, developing, and yet to be initiated. This work also sets out to highlight potential difficulties and formulate recommendations for successful BVD control. It concludes that a systematic, countrywide approach is needed to achieve a sustainable decrease in BVD prevalence. The role of vaccines in control programs is concluded to be a valuable additional biosecurity measure. This study also concludes that there are potential wider benefits to a systematic BVD control program, such as a reduction in antimicrobial use and increases in the competitiveness of the cattle industry.

A new bovine tuberculosis model for England and Wales (BoTMEW) to simulate epidemiology, surveillance and control

BACKGROUND

Bovine tuberculosis (bTB) is a zoonotic disease of cattle caused by Mycobacterium bovis, widespread in England and Wales. It has high incidence towards the South West of England and Wales, with much lower incidence to the East and North. A stochastic simulation model was developed to simulate M. bovis transmission among cattle, transfer by cattle movements and transmission from environmental reservoirs (often wildlife and especially badgers). It distinguishes five surveillance streams, including herd tests, pre-movement testing and slaughter surveillance. The model thereby simulates interventions in bTB surveillance and control, and generates outputs directly comparable to detailed disease records. An anonymized version of the executable model with its input data has been released. The model was fitted to cattle bTB records for 2008-2010 in a cross-sectional comparison, and its projection was compared with records from 2010 to 2016 for validation.

RESULTS

The fitted model explained over 99% of the variation among numbers of breakdowns in four defined regions and surveillance streams in 2010. It classified 7800 (95% confidence interval c. 5500 - 14,000) holdings within high incidence regions as exposed to infectious environmental reservoirs, out of over 31,000 cattle holdings identified as potentially exposed to such sources. The model was consistent with previous estimates of low M. bovis transmission rate among cattle, but cattle to cattle transmission was clearly required to generate the number of cattle cases observed. When projected to 2016, the model as fitted to 2010 continued to match the distribution of bTB among counties, although it was notable that the actual distribution of bTB in 2010 was itself a close match for its distribution in 2016.

CONCLUSIONS

The close model fit demonstrated that cattle movements could generate breakdowns as observed in low incidence regions, if persistent environmental reservoirs such as wildlife maintained infection levels in the high incidence regions. The model suggests that environmental reservoirs may be a challenge for control, because, although many holdings are exposed to infection from wildlife or the environment, they are a minority of holdings. Large impacts on disease in wildlife will be required to avoid each individual transmission event to cattle.

Abrupt events and population synchrony in the dynamics of Bovine Tuberculosis

Disease control strategies can have both intended and unintended effects on the dynamics of infectious diseases. Routine testing for the harmful pathogen Bovine Tuberculosis (bTB) was suspended briefly during the foot and mouth disease epidemic of 2001 in Great Britain. Here we utilize bTB incidence data and mathematical models to demonstrate how a lapse in management can alter epidemiological parameters, including the rate of new infections and duration of infection cycles. Testing interruption shifted the dynamics from annual to 4-year cycles, and created long-lasting shifts in the spatial synchrony of new infections among regions of Great Britain. After annual testing was introduced in some GB regions, new infections have become more de-synchronised, a result also confirmed by a stochastic model. These results demonstrate that abrupt events can synchronise disease dynamics and that changes in the epidemiological parameters can lead to chaotic patterns, which are hard to be quantified, predicted, and controlled.

The disease dynamics of bovine tuberculosis have been of interest given the pathogen’s effect on wild animal and livestock health. Here, the authors show that a brief cessation of testing for bovine tuberculosis in 2001 altered the population synchrony of the disease dynamics across regions of Great Britain.

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

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Bovine tuberculosis elevated-risk areas historically more extensive than thought.

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Cattle movements alone do not explain spread of areas of elevated risk.

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For all genotypes, the majority of infection spread is due to local effects.

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Similar risk-factors identified within elevated-risk and transitional areas.

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Risk factors key to identify incipient elevated-risk areas before incidence rising.

Bovine tuberculosis (bTB) is a chronic zoonosis with major health and economic impact on the cattle industry. Despite extensive control measures in cattle and culling trials in wildlife, the reasons behind the expansion of areas with high incidence of bTB breakdowns in Great Britain remain unexplained. By balancing the importance of cattle movements and local transmission on the observed pattern of cattle outbreaks, we identify areas at elevated risk of infection from specific Mycobacterium bovis genotypes. We show that elevated-risk areas (ERAs) were historically more extensive than previously understood, and that cattle movements alone are insufficient for ERA spread, suggesting the involvement of other factors. For all genotypes, we find that, while the absolute risk of infection is higher in ERAs compared to areas with intermittent risk, the statistically significant risk factors are remarkably similar in both, suggesting that these risk factors can be used to identify incipient ERAs before this is indicated by elevated incidence alone. Our findings identify research priorities for understanding bTB dynamics, improving surveillance and guiding management to prevent further ERA expansion.

Rumen fluke (Calicophoron daubneyi) on Welsh farms: prevalence, risk factors and observations on co-infection with Fasciola hepatica

Reports of Calicophoron daubneyi infecting livestock in Europe have increased substantially over the past decade; however, there has not been an estimate of its farm level prevalence and associated risk factors in the UK. Here, the prevalence of C. daubneyi across 100 participating Welsh farms was recorded, with climate, environmental and management factors attained for each farm and used to create logistic regression models explaining its prevalence. Sixty-one per cent of farms studied were positive for C. daubneyi, with herd-level prevalence for cattle (59%) significantly higher compared with flock-level prevalence for sheep (42%, P = 0·029). Co-infection between C. daubneyi and Fasciola hepatica was observed on 46% of farms; however, a significant negative correlation was recorded in the intensity of infection between each parasite within cattle herds (rho = −0·358, P = 0·007). Final models showed sunshine hours, herd size, treatment regularity against F. hepatica, the presence of streams and bog habitats, and Ollerenshaw index values as significant positive predictors for C. daubneyi (P < 0·05). The results raise intriguing questions regarding C. daubneyi epidemiology, potential competition with F. hepatica and the role of climate change in C. daubneyi establishment and its future within the UK.

The effects of pre-slaughter restraint (for the purpose of cattle identification) on post-slaughter responses and carcass quality following the electrical stun/killing of cattle in a Jarvis Beef stunner

This study compared normal post-Jarvis stun/kill responses and carcass quality with those occurring when crush restraint was not used during pre-slaughter. The carcasses of 1065 cattle slaughtered during one week at a commercial abattoir were evaluated for quality. The post-stun/kill responses of 788 of these animals were also assessed. An additional study of data from the carcasses of 6061 cattle was further evaluated for quality findings. A significant reduction in post-stun/kill limb movement, muscle tone and the expression of brainstem functions was recorded when restraint was not used. Abolishing crush restraint pre-slaughter also produced a significant reduction in the incidence of blood splash. In addition, the study also showed that animal identification post-slaughter could be successfully implemented with no negative consequences to food safety or traceability. It is suggested that abolishing the use of pre-slaughter crush restraint of cattle would enhance animal welfare and operator safety in plants whether electrical, or mechanical stunning was employed.

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.

Not all cows are epidemiologically equal: quantifying the risks of bovine viral diarrhoea virus (BVDV) transmission through cattle movements

Many economically important cattle diseases spread between herds through livestock movements. Traditionally, most transmission models have assumed that all purchased cattle carry the same risk of generating outbreaks in the destination herd. Using data on bovine viral diarrhoea virus (BVDV) in Scotland as a case example, this study provides empirical and theoretical evidence that the risk of disease transmission varies substantially based on the animal and herd demographic characteristics at the time of purchase. Multivariable logistic regression analysis revealed that purchasing pregnant heifers and open cows sold with a calf at foot were associated with an increased risk of beef herds being seropositive for BVDV. Based on the results from a dynamic within-herd simulation model, these findings may be partly explained by the age-related probability of animals being persistently infected with BVDV as well as the herd demographic structure at the time of animal introductions. There was also evidence that an epidemiologically important network statistic, "betweenness centrality" (a measure frequently associated with the potential for herds to acquire and transmit disease), was significantly higher for herds that supplied these particular types of replacement beef cattle. The trends for dairy herds were not as clear, although there was some evidence that open heifers and open lactating cows were associated with an increased risk of BVDV. Overall, these findings have important implications for developing simulation models that more accurately reflect the industry-level transmission dynamics of infectious cattle diseases.

Exploring cattle movements in Belgium

Movement of animals from one farm to another is a potential risk and can lead to the spreading of livestock diseases. Therefore, in order to implement effective control measures, it is important to understand the movement network in a given area. Using the SANITEL data from 2005 to 2009, around 2 million cattle movements in Belgium were traced. Exploratory analysis revealed different spatial structures for the movement of different cattle types: fattening calves are mostly moved to the Antwerp region, adult cattle are moved to different parts in Belgium. Based on these differences, movement of cattle would more likely cause a spread of disease to a larger number of areas in Belgium as compared to the fattening calves. A closer inspection of the spatial and temporal patterns of cattle movement using a weighted negative binomial model, revealed a significant short-distance movement of bovine which could be an important factor contributing to the local spreading of a disease. The model however revealed hot spot areas of movement in Belgium; four areas in the Walloon region (Luxembourg, Hainaut, Namur and Liege) were found as hot spot areas while East and West Flanders are important "receivers" of movement. This implies that an introduction of a disease to these Walloon regions could result in a spread toward the East and West Flanders regions, as what happened in the case of Bluetongue BTV-8 outbreak in 2006. The temporal component in the model also revealed a linear trend and short- and long-term seasonality in the cattle movement with a peak around spring and autumn. The result of this explorative analysis enabled the identification of "hot spots" in time and space which is important in enhancing any existing monitoring and surveillance system.

E. coli O157 on Scottish cattle farms: evidence of local spread and persistence using repeat cross-sectional data

Background

Escherichia coli (E. coli) O157 is a virulent zoonotic strain of enterohaemorrhagic E. coli. In Scotland (1998-2008) the annual reported rate of human infection is 4.4 per 100,000 population which is consistently higher than other regions of the UK and abroad. Cattle are the primary reservoir. Thus understanding infection dynamics in cattle is paramount to reducing human infections.

A large database was created for farms sampled in two cross-sectional surveys carried out in Scotland (1998 - 2004). A statistical model was generated to identify risk factors for the presence of E. coli O157 on farms. Specific hypotheses were tested regarding the presence of E. coli O157 on local farms and the farms previous status. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred.

Results

The presence of an E. coli O157 positive local farm (average distance: 5.96km) in the Highlands, North East and South West, farm size and the number of cattle moved onto the farm 8 weeks prior to sampling were significant risk factors for the presence of E. coli O157 on farms. Previous status of a farm was not a significant predictor of current status (p = 0.398). Farms within the same sampling cluster were significantly more likely to be the same PFGE type (p < 0.001), implicating spread of strains between local farms. Isolates with identical PFGE types were observed to persist across the two surveys, including 3 that were identified on the same farm, suggesting an environmental reservoir. PFGE types that were persistent were more likely to have been observed in human clinical infections in Scotland (p < 0.001) from the same time frame.

Conclusions

The results of this study demonstrate the spread of E. coli O157 between local farms and highlight the potential link between persistent cattle strains and human clinical infections in Scotland. This novel insight into the epidemiology of Scottish E. coli O157 paves the way for future research into the mechanisms of transmission which should help with the design of control measures to reduce E. coli O157 from livestock-related sources.

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

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

Suboptimal herd performance amplifies the spread of infectious disease in the cattle industry

Farms that purchase replacement breeding cattle are at increased risk of introducing many economically important diseases. The objectives of this analysis were to determine whether the total number of replacement breeding cattle purchased by individual farms could be reduced by improving herd performance and to quantify the effects of such reductions on the industry-level transmission dynamics of infectious cattle diseases. Detailed information on the performance and contact patterns of British cattle herds was extracted from the national cattle movement database as a case example. Approximately 69% of beef herds and 59% of dairy herds with an average of at least 20 recorded calvings per year purchased at least one replacement breeding animal. Results from zero-inflated negative binomial regression models revealed that herds with high average ages at first calving, prolonged calving intervals, abnormally high or low culling rates, and high calf mortality rates were generally more likely to be open herds and to purchase greater numbers of replacement breeding cattle. If all herds achieved the same level of performance as the top 20% of herds, the total number of replacement beef and dairy cattle purchased could be reduced by an estimated 34% and 51%, respectively. Although these purchases accounted for only 13% of between-herd contacts in the industry trade network, they were found to have a disproportionately strong influence on disease transmission dynamics. These findings suggest that targeting extension services at herds with suboptimal performance may be an effective strategy for controlling endemic cattle diseases while simultaneously improving industry productivity.

Dynamics of infectious diseases

Modern infectious disease epidemiology has a strong history of using mathematics both for prediction and to gain a deeper understanding. However the study of infectious diseases is a highly interdisciplinary subject requiring insights from multiple disciplines, in particular a biological knowledge of the pathogen, a statistical description of the available data and a mathematical framework for prediction. Here we begin with the basic building blocks of infectious disease epidemiology--the SIS and SIR type models--before considering the progress that has been made over the recent decades and the challenges that lie ahead. Throughout we focus on the understanding that can be developed from relatively simple models, although accurate prediction will inevitably require far greater complexity beyond the scope of this review. In particular, we focus on three critical aspects of infectious disease models that we feel fundamentally shape their dynamics: heterogeneously structured populations, stochasticity and spatial structure. Throughout we relate the mathematical models and their results to a variety of real-world problems.

Bovine tuberculosis and badgers in Britain: relevance of the past

The European badger (Meles meles) has been identified as a wildlife reservoir of bovine tuberculosis and a source of transmission to cattle in Britain and Ireland. Both behavioural ecology and statistical ecological modelling have indicated the long-term persistence of the disease in some badger communities, and this is postulated to account for the high incidence of bovine tuberculosis in cattle across large tracts of England and Wales. This paper questions this consensus by using historical cartographic evidence to show that tuberculosis in cattle had a very different spatial distribution before 1960 to the present day. Since few of the badgers collected in road traffic accidents between 1972 and 1990 had tuberculosis in counties such as Cheshire, where the disease had until shortly before that been rife in the cattle population, the role of badgers as reservoirs in spreading disease in similar counties outside the south-west of England has to be questioned.

Trânsito de bovinos nos estados do Mato Grosso e Mato Grosso do Sul, Brasil

Compreender a dinâmica de atuação dos frigoríficos contribui para a definição de prioridades e para o estabelecimento de barreiras sanitárias, em caso de uma possível emergência sanitária, ou para a busca de estratégias para a erradicação de enfermidades bovinas. O objetivo deste estudo foi analisar e descrever as áreas de abrangência dos principais municípios que possuem frigoríficos de abate de bovinos com serviço de inspeção federal nos estados do Mato Grosso e Mato Grosso do Sul, revelando as peculiaridades do trânsito bovino. Os dados para execução do estudo, fornecidos pelo Ministério da Agricultura, Pecuária e Abastecimento, foram trabalhados espacialmente e por meio de redes de fluxo.As técnicas de geoprocessamento revelaram as regiões de atuação dos frigoríficos dos principais municípios de destino dos dois estados, no entanto no Mato Grosso a segmentação é mais fácil de ser notada do que no Mato Grosso do Sul. Os resultados sugerem maior regionalização dos polos de abate do Mato Grosso, com regiões de atuação dos frigoríficos bem definidas, e menor comunicação entre os polos de abate. Já no Mato Grosso do Sul, o fluxo, muito intenso, está direcionado para a região central do estado, favorecendo a interação maior entre os municípios.

Spread of E. coli O157 infection among Scottish cattle farms: stochastic models and model selection

Identifying risk factors for the presence of Escherichia coli O157 infection on cattle farms is important for understanding the epidemiology of this zoonotic infection in its main reservoir and for informing the design of interventions to reduce the public health risk. Here, we use data from a large-scale field study carried out in Scotland to fit both "SIS"-type dynamical models and statistical risk factor models. By comparing the fit (assessed using maximum likelihood) of different dynamical models we are able to identify the most parsimonious model (using the AIC statistic) and compare it with the model suggested by risk factor analysis. Both approaches identify 2 key risk factors: the movement of cattle onto the farm and the number of cattle on the farm. There was no evidence for a role of other livestock species or seasonality, or of significant risk of local spread. However, the most parsimonious dynamical model does predict that farms can infect other farms through routes other than cattle movement, and that there is a nonlinear relationship between the force of infection and the number of infected farms. An important prediction from the most parsimonious model is that although only approximately 20% farms may harbour E. coli O157 infection at any given time approximately 80% may harbour infection at some point during the course of a year.

A "shotgun" method for tracing the birth locations of sheep from flock tags, applied to scrapie surveillance in Great Britain

Movement records are often used to identify animal sample provenance by retracing the movements of individuals. Here we present an alternative method, which uses the same identity tags and movement records as are used to retrace movements, but ignores individual movement paths. The first step uses a simple query to identify the most likely birth holding for every identity tag included in a database recording departures from agricultural holdings. The second step rejects a proportion of the birth holding locations to leave a list of birth holding locations that are relatively reliable. The method was used to trace the birth locations of sheep sampled for scrapie in abattoirs, or on farm as fallen stock. Over 82% of the sheep sampled in the fallen stock survey died at the holding of birth. This lack of movement may be an important constraint on scrapie transmission. These static sheep provided relatively reliable birth locations, which were used to define criteria for selecting reliable traces. The criteria rejected 16.8% of fallen stock traces and 11.9% of abattoir survey traces. Two tests provided estimates that selection reduced error in fallen stock traces from 11.3% to 3.2%, and in abattoir survey traces from 8.1% to 1.8%. This method generated 14,591 accepted traces of fallen stock from samples taken during 2002-2005 and 83,136 accepted traces from abattoir samples. The absence or ambiguity of flock tag records at the time of slaughter prevented the tracing of 16-24% of abattoir samples during 2002-2004, although flock tag records improved in 2005. The use of internal scoring to generate and evaluate results from the database query, and the confirmation of results by comparison with other database fields, are analogous to methods used in web search engines. Such methods may have wide application in tracing samples and in adding value to biological datasets.

Herd size and bovine tuberculosis persistence in cattle farms in Great Britain

Bovine tuberculosis (bTB) infection in cattle is one of the most complex and persistent problems faced by the cattle industry in Great Britain today. While a number of factors have been identified as increasing the risk of infection, there has been little analysis on the causes of persistent infection within farms. In this article, we use the Cattle Tracing System to examine changes in herd size and VetNet data to correlate herd size with clearance of bTB. We find that the number of active farms fell by 16.3% between 2002 and 2007. The average farm size increased by 17.9% between 2002 and 2005. Using a measure similar to the Critical Community Size, the VetNet data reveal that herd size is positively correlated with disease persistence. Since economic policy and subsidies have been shown to influence farm size, we used a simple financial model for ideal farm size which includes disease burden to conclude that increasing herd size for efficiency gains may contribute to increased disease incidence.

Exploring the role of auction markets in cattle movements within Great Britain

Within Great Britain cattle are often traded at regional markets, of which there are approximately 200 located throughout England, Scotland and Wales. The movement of animals through markets was important in the spread of foot-and-mouth disease (FMD) virus during the 2001 GB outbreak. Here, we describe the movements of cattle to and from markets for 2002-2004 and, using social network analysis, we construct networks based on these movements. In 2002, 56,227 animal holdings (AH) sent cattle to 222 cattle auction markets, compared to 58,476 AH and 187 auction markets in 2004. Auction markets vary considerably in their trading with AH. The majority of markets received animals from less than 50 AH, but one received animals from as many as 6155 AH during a year. The distances travelled between origin AH and destination AH when cattle move "directly" were found to be significantly shorter compared to distances between origin and destination AH where the movement occurred via a market. However, the vast majority of distances moved, for both types of movements, were less than 50 km. Some auction markets appear as highly connected premises within the contact network and are associated with high betweenness scores. However AH also occupy positions central to the contact network. The variation in the characteristics and role of individual markets within the contact network suggests important differences in risk of disease transmission associated with each market. Inclusion of network parameters, when considering the risk associated with moving cattle through auction markets may enhance the development of effective targeted disease control strategies.

Recent network evolution increases the potential for large epidemics in the British cattle population

Following the foot and mouth disease epidemic in Great Britain (GB) in 2001, livestock movement bans were replaced with mandatory periods of standstill for livestock moving between premises. It was anticipated that these movement restrictions would limit each individual's contact networks, the extent of livestock movements and thus the spread of future disease outbreaks. However, the effect of behaviour changes on the global network in adapting to these restrictions is currently unknown. Here, we take a novel approach using GB cattle movement data to construct week-by-week contact networks between animal holdings (AH) to explore the evolution of the network since this policy was introduced, the first time network theory has been used for this purpose. We show that the number of AH moving cattle as part of the giant strong component (GSC), representing the region of maximal connectivity, has been increasing linearly over time. This is of epidemiological significance as the size of the GSC indicates the number of holdings potentially exposed to disease, thus giving a lower bound of maximum epidemic size. Therefore, despite restriction of cattle movements, emergent behaviour in this self-organizing system has potentially increased the size of infectious disease epidemics within the cattle industry.

Identifying temporal variation in reported births, deaths and movements of cattle in Britain

Background

The accuracy of predicting disease occurrence using epidemic models relies on an understanding of the system or population under investigation. At the time of the Foot and Mouth disease (FMD) outbreak of 2001, there were limited reports in the literature as to the cattle population structure in Britain. In this paper we examine the temporal patterns of cattle births, deaths, imports and movements occurring within Britain, reported to the Department for the Environment, Food and Rural Affairs (DEFRA) through the British Cattle Movement service (BCMS) during the period 1^st January 2002 to 28^th February 2005.

Results

In Britain, the number of reported cattle births exhibit strong seasonality characterised by a large spring peak followed by a smaller autumn peak. Other event types also exhibit strong seasonal trends; both the reported number of cattle slaughtered and "on-farm" cattle deaths increase during the final part of the year. After allowing for seasonal components by smoothing the data, we illustrate that there is very little remaining non-seasonal trend in the number of cattle births, "on-farm" deaths, slaughterhouse deaths, on- and off-movements. However after allowing for seasonal fluctuations the number of cattle imports has been decreasing since 2002. Reporting of movements, births and deaths was more frequent on certain days of the week. For instance, greater numbers of cattle were slaughtered on Tuesdays, Wednesdays and Thursdays. Evidence for digit preference was found in the reporting of births and "on-farm" deaths with particular bias towards over reporting on the 1^st, 10^th and 20^th of each month.

Conclusion

This study provides insight into the population and movement dynamics of the British cattle population. Although the population is in constant flux, seasonal and long term trends can be identified in the number of reported births, deaths and movements of cattle. Incorporating this temporal variation in epidemic disease modelling may result in more accurate model predictions and may usefully inform future surveillance strategies.

Cattle movements and bovine tuberculosis in Great Britain

For 20 years, bovine tuberculosis (BTB) has been spreading in Great Britain (England, Wales and Scotland) and is now endemic in the southwest and parts of central England and in southwest Wales, and occurs sporadically elsewhere. Although its transmission pathways remain poorly understood, the disease's distribution was previously modelled statistically by using environmental variables and measures of their seasonality. Movements of infected animals have long been considered a critical factor in the spread of livestock diseases, as reflected in strict import/export regulations, the extensive movement restrictions imposed during the 2001 foot-and-mouth disease outbreak, the tracing procedures after a new case of BTB has been confirmed and the Government's recently published strategic framework for the sustainable control on BTB. Since January 2001 it has been mandatory for stock-keepers in Great Britain to notify the British Cattle Movement Service of all cattle births, movements and deaths. Here we show that movements as recorded in the Cattle Tracing System data archive, and particularly those from areas where BTB is reported, consistently outperform environmental, topographic and other anthropogenic variables as the main predictor of disease occurrence. Simulation distribution models for 2002 and 2003, incorporating all predictor categories, are presented and used to project distributions for 2004 and 2005.