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.     

Effect of creep partitions on teat-seeking behavior of newborn piglets

In the first of two studies on teat-seeking behavior of newborn pigs, latencies from birth to first mammary contact (LMC) and to first suckle (LS) were recorded by live observation (n = 66). LMC accounted for 66% of LS and variances were similar between these two measures, suggesting that LMC is a good predictor of time to first suckle. In a second experiment, 32 litters of pigs were farrowed in crates equipped with either solid, vertically slatted, horizontally slatted or diamond mesh creep partitions. Piglet behavior following parturition was recorded via time-lapse videotape. LMC was determined for each piglet and movements were plotted for four focal pigs/litter. Partition type did not affect LMC (mean = 34 min). LMC was significantly affected by number of littermates present during teat-seeking (P less than .001), birth order (P less than .001) and frequency of position changes by the sow (r = .26, P less than .01). Neither sex nor birth weight affected LMC on a within-litter basis, but across litters smaller pigs had greater contact latencies (r = -.38, P less than .001). Partition type did not affect distance traveled or time spent in contact with the sow, in contact with the creep partitions,, free standing or the total of these. LMC was positively correlated (P less than .05) with contact time with the sow (r = .34) and time behind the sow's back (r = .38) and negatively correlated with time spent free standing (r = -.35, P less than .05) and in contact with the sow's rear legs (r = -.29; P less than .10).     

Estimating potential epidemic size following introduction of a long-incubation disease in scale-free connected networks of milking-cow movements in Ontario, Canada

We used the movements of adult milking cows among farms enrolled in the Dairy Herd Improvement (DHI) program in Ontario to explore the size of an epidemic that might result from farm-to-farm movements of cows in the Province if a reportable long-incubation infection like tuberculosis (TB) were introduced and not detected for 1-3 years after introduction. A directed network was created for each year (2004-2006) using all pairs of individual shipments, defined as the movement of one or more cows on a single day, from a single source DHI farm to a single recipient DHI farm. A 3-year network was also developed that included all cow shipments that took place during these 3 years. The lower and upper bounds of potential maximal epidemic size were estimated using four network-analysis measures: (1) the farm out-degree, (2) the size of the largest strong and weak components, (3) the bow-tie approach, classifying farms into six different areas of a directed network and (4) the infection chain of a farm. All four of the DHI movement networks were found to be small-world, indicating that infection could spread over considerable distances by shipments that linked potentially distant clusters of farms. The networks were also scale-free, indicating most farms had relatively few connections to other farms, while there were a few highly connected farms. Characterization of the yearly networks showed that 41-47% of DHI farms were not involved in any cow shipments and were therefore not at risk of infection from this movement network; furthermore, if infection were introduced into a DHI farm that shipped animals that year, the infection would have stopped at that farm (or at least, not been passed on by shipment of adult milking cows) >50% of the time, and 75% of the time only one more DHI farm would have become infected through animal movements. Compared to the infection chain, which accounted for both the direction and the time sequence of shipments in the movement network, the other network-analysis measures provided biased estimates of potential epidemic size. The bow-tie approach provided a schematic representation of the level of risk of each farm in the network in spreading an infection, but overestimated the lower- and upper-bound measures of potential epidemic size because it did not account for the time sequence of shipments. Our infection-chain results suggest that introducing a long-incubation disease into the network of farms enrolled in the DHI program in Ontario that was not identified until 12 months after the incursion would, in a worst-case scenario, have resulted in 168 farms (representing 5% of all Ontario DHI herds) being infected as a consequence of adult cow movements among DHI farms. This estimate increased to 850 farms (26% of all DHI herds) if the infection were not identified for 36 months.     

Characteristics of the spatio-temporal network of cattle movements in France over a 5-year period

A good knowledge of the specificities of the animal trade network is highly valuable to better control pathogen spread on a large regional to transnational scale. Because of their temporal dynamical nature, studying multi-annual datasets is particularly needed to investigate whether structural patterns are stable over the years. In this study, we analysed the French cattle movement network from 2005 to 2009 for different spatial granularities and temporal windows, with the three-fold objective of exploring temporal variations of the main network characteristics, computing proxies for pathogen spread on this network, which accounts for its time-varying properties and identifying specificities related to the main types of animals and farms (dairy versus beef). Network properties did not qualitatively vary among different temporal and spatial granularities. About 40% of the holdings and 80% of the communes were directly interconnected. The width of the aggregation time window barely impacted normalised distributions of indicators. A period of 8–16 weeks would suffice for robust estimation of their main trends, whereas longer periods would provide more details on tails. The dynamic nature of the network could be seen through the small overlap between consecutive networks with 65% of common active nodes for only 3% of common links over 2005–2009. To control pathogen spread on such a network, by reducing the largest strongly connected component by more than 80%, movements should be prevented from 1 to 5% of the holdings with the highest centrality in the previous year network. The analysis of breed-wise and herd-wise subnetworks, dairy, beef and mixed, reveals similar trends in temporal variation of average indicators and their distributions. The link-based backbones of beef subnetworks seem to be more stable over time than those of other subnetworks. At a regional scale, node reachability accounting for time-respecting paths, as proxy of epidemic burden, is greater for a dairy region than for a beef region. This highlights the importance of considering local specificities and temporal dynamics of animal trade networks when evaluating control measures of pathogen spread.     

A novel method to identify herds with an increased probability of disease introduction due to animal trade

In the design of surveillance, there is often a desire to target high risk herds. Such risk-based approaches result in better allocation of resources and improve the performance of surveillance activities. For many contagious animal diseases, movement of live animals is a main route of transmission, and because of this, herds that purchase many live animals or have a large contact network due to trade can be seen as a high risk stratum of the population. This paper presents a new method to assess herd disease risk in animal movement networks. It is an improvement to current network measures that takes direction, temporal order, and also movement size and probability of disease into account. In the study, the method was used to calculate a probability of disease ratio (PDR) of herds in simulated datasets, and of real herds based on animal movement data from dairy herds included in a bulk milk survey for Coxiella burnetii. Known differences in probability of disease are easily incorporated in the calculations and the PDR was calculated while accounting for regional differences in probability of disease, and also by applying equal probability of disease throughout the population. Each herd's increased probability of disease due to purchase of animals was compared to both the average herd and herds within the same risk stratum. The results show that the PDR is able to capture the different circumstances related to disease prevalence and animal trade contact patterns. Comparison of results based on inclusion or exclusion of differences in risk also highlights how ignoring such differences can influence the ability to correctly identify high risk herds. The method shows a potential to be useful for risk-based surveillance, in the classification of herds in control programmes or to represent influential contacts in risk factor studies.     

Influence of contact heterogeneity on TB reproduction ratio R0 in a free-living brushtail possum Trichosurus vulpecula population

Social network analyses were used to investigate contact patterns in a free-living possum Trichosurus vulpecula population and to estimate the influence of contact on R(0) for bovine tuberculosis (TB). Using data collected during a five-year capture-mark-recapture study of a free-living possum population, observed estimates of R(0) were computed and compared with R(0) computed from random networks of similar size that approximated a random mixing process. All networks displayed a heterogeneous pattern of contact with the average number of contacts per possum ranging from 20 to 26 per year. The networks consistently showed small-world and single-scale features. The mean estimates of R(0) for TB using the observed contact networks were 1.78, 1.53, 1.53, 1.51, and 1.52 times greater than the corresponding random networks (P <0.05). We estimate that TB would spread if an average of between 1.94 and 1.97 infective contacts occurred per year per infected possum, which is approximately half of that expected from a random network. These results have implications for the management of TB in New Zealand where the possum is the principal wildlife reservoir host of Mycobacterium bovis, the causal agent of bovine TB. This study argues the relevance of refining epidemiological models used to inform disease management policy to account for contact heterogeneity.     

Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks

A new method for the calculation of a centrality measure (Disease Flow Centrality, DFC), which takes into account temporal dynamics of livestock movement networks, is proposed. The method is based on a network traversal algorithm which represents an epidemic process more realistically compared with traditional graph traversal algorithms used in the calculation of centrality measures on static networks. The new approach was tested on networks generated from all the registered movements of cattle in Italy in the years 2007, 2008 and 2009 and the results were compared to those obtained by classical centrality measures. The results show that DFC values often differ substantially from those of other centrality measures and that these DFC values tend to be more unstable in time. The DFC offers several advantages for assessing risk and vulnerability of specific holdings and of an entire network, using recent movement data from national livestock databases. Some examples also indicate how the basic approach in the DFC calculation could be expanded into a more complex epidemic model by incorporating weights and how it could be combined with a geo-spatial perspective.     

Models to capture the potential for disease transmission in domestic sheep flocks

Successful control of livestock diseases requires an understanding of how they spread amongst animals and between premises. Mathematical models can offer important insight into the dynamics of disease, especially when built upon experimental and/or field data. Here the dynamics of a range of epidemiological models are explored in order to determine which models perform best in capturing real-world heterogeneities at sufficient resolution. Individual based network models are considered together with one- and two-class compartmental models, for which the final epidemic size is calculated as a function of the probability of disease transmission occurring during a given physical contact between two individuals. For numerical results the special cases of a viral disease with a fast recovery rate (foot-and-mouth disease) and a bacterial disease with a slow recovery rate (brucellosis) amongst sheep are considered. Quantitative results from observational studies of physical contact amongst domestic sheep are applied and results from the differently structured flocks (ewes with newborn lambs, ewes with nearly weaned lambs and ewes only) compared. These indicate that the breeding cycle leads to significant changes in the expected basic reproduction ratio of diseases. The observed heterogeneity of contacts amongst animals is best captured by full network simulations, although simple compartmental models describe the key features of an outbreak but, as expected, often overestimate the speed of an outbreak. Here the weights of contacts are heterogeneous, with many low weight links. However, due to the well-connected nature of the networks, this has little effect and differences between models remain small. These results indicate that simple compartmental models can be a useful tool for modelling real-world flocks; their applicability will be greater still for more homogeneously mixed livestock, which could be promoted by higher intensity farming practices.     

The blood vessels of the mesonephros of domestic cattle (Bos taurus), a corrosion cast study

The blood vessels of the bovine mesonephros - a corrosion cast study Using scanning electron microscopy plastoid corrosion cast specimens of the mesonephros of 30-45-day-old bovine foetuses were investigated. The studies showed that the blood vessels of the mesonephros are organized in two separate networks similar to these of the teleosts and amphibians. The glomerula mesonephrica originate from the aorta implying that they belong to the high pressure system. The tubuli mesonephrici are surrounded by a filamentous independent capillary network which is shown for the first time in these studies. This capillary network originates from the caudal cardinal veins and represents a mesonephric portal system with a relatively low blood pressure. The blood from the two capillary networks diverts into terminal veins and into the subcardinal veins. The questions of haemodynamics in the mesonephros are discussed.     

Contact patterns as a risk factor for bovine tuberculosis infection in a free-living adult brushtail possum Trichosurus vulpecula population

The aim of this study was to identify risk factors for bovine tuberculosis (TB) in a free-roaming, capture-mark-recapture monitored possum Trichosurus vulpecula population in a 22-ha study site at Castlepoint, New Zealand from 1 April 1989 to 31 March 1994. A matched case-control design was used to evaluate the influence of sex, habitat and contact opportunities on TB risk. Cases comprised possums identified as TB-positive throughout the study period. Controls were selected from the group of possums that were captured and showed no clinical signs of TB throughout the study period. Measures derived from a social network analysis of possum capture locations such as degree, clustering coefficient (CC) and betweenness were used to represent potential contact opportunities among possums. Network analysis measures recorded for individual possums in the 12-month period before a diagnosis of TB were evaluated in a conditional logistic regression model. We found no evidence of an association between case status and the total number of possums with which there was potential contact (degree) (P=0.5). The odds of cases being exposed to unit increases in the number of TB-positive contacts was 2.50 (95% CI 1.24-5.05; P<0.01) times that of controls. This effect was conditional on the total number of potential contacts made, with a negative interaction with increasing degree. These findings indicate that potential contact with TB-positive possums increases the odds of disease whereas potential contact with large numbers of possums does not. This suggests that multiple contacts with TB-positive possum(s) are necessary for transmission of TB and this is more likely to occur in networks that are smaller. We challenge the hypothesis that contact with large numbers of individuals increases the probability of becoming TB infected and argue that individual contact behaviour is a determinant of the creation of TB foci within free-living possum populations.     

Social Network Analysis for Assessment of Avian Influenza Spread and Trading Patterns of Backyard Chickens in Nakhon Pathom,Suphan Buri and Ratchaburi,Thailand

The aim of this study is to explain the social networks of the backyard chicken in Ratchaburi, Suphan Buri and Nakhon Pathom Provinces. In this study, we designed the nodes as groups of persons or places involved in activities relating to backyard chickens. The ties are all activities related to the nodes. The study applied a partial network approach to assess the spreading pattern of avian influenza. From 557 questionnaires collected from the nodes, the researchers found that the degree (the numbers of ties that a node has) and closeness (the distance from one node to the others) centralities of Nakhon Pathom were significantly higher than those of the others (P < 0.001). The results show that compared with the remaining areas, this area is more quickly connected to many links. If the avian influenza virus subtype H5N1 was released into the network, the disease would spread throughout this province more rapidly than in Ratchaburi and Suphan Buri. The betweenness centrality in each of these provinces showed no differences (P > 0.05). In this study, the nodes that play an important role in all networks are farmers who raise consumable chicken, farmers who raise both consumable chicken and fighting cocks, farmers’ households that connect with dominant nodes, and the owners and observers of fighting cocks at arenas and training fields. In this study, we did not find cut points or blocks in the network. Moreover, we detected a random network in all provinces. Thus, connectivity between the nodes covers long or short distances, with less predictable behaviour. Finally, this study suggests that activities between the important nodes must receive special attention for disease control during future disease outbreaks.     

Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling

Between holding contacts are more common over short distances and this may have implications for the dynamics of disease spread through these contacts. A reliable estimation of how contacts depend on distance is therefore important when modeling livestock diseases. In this study, we have developed a method for analyzing distant dependent contacts and applied it to animal movement data from Sweden. The data were analyzed with two competing models. The first model assumes that contacts arise from a purely distance dependent process. The second is a mixture model and assumes that, in addition, some contacts arise independent of distance. Parameters were estimated with a Bayesian Markov Chain Monte Carlo (MCMC) approach and the model probabilities were compared. We also investigated possible between model differences in predicted contact structures, using a collection of network measures.We found that the mixture model was a much better model for the data analyzed. Also, the network measures showed that the models differed considerably in predictions of contact structures, which is expected to be important for disease spread dynamics. We conclude that a model with contacts being both dependent on, and independent of, distance was preferred for modeling the example animal movement contact data.     

An attempt to estimate students' workload

Following the recent introduction of the European Credit Transfer System (ECTS) into several European university programs, a new interest has developed in determining students' workload. ECTS credits are numerical values describing the student workload required to complete course units; ECTS has the potential to facilitate comparison and create transparency between institutional curricula. ECTS credits are frequently listed alongside institutional credits in course outlines and module summaries. Measuring student workload has been difficult; to a large extent, estimates are based only upon anecdotal and casual information. To gather more systematic information, we asked students at the Veterinary Faculty, University of Ljubljana, to estimate the actual total workload they committed to fulfill their coursework obligations for specific subjects in the veterinary degree program by reporting their attendance at defined contact hours and their estimated time for outside study, including the time required for examinations and other activities. Students also reported the final grades they received for these subjects. The results show that certain courses require much more work than others, independent of credit unit assignment. Generally, the courses with more contact hours tend also to demand more independent work; the best predictor of both actual student workload and student success is the amount of contact time in which they participate. The data failed to show any strong connection between students' total workload and grades they received; rather, they showed some evidence that regular presence at contact hours was the most positive influence on grades. Less frequent presence at lectures tended to indicate less time spent on independent study. It was also found that pre-clinical and clinical courses tended to require more work from students than other, more general subjects. While the present study does not provide conclusive evidence, it does indicate the need for further inquiry into the nature of the relationship between teaching and learning in higher education and for evaluation of the benefits (or otherwise) of more "self-directed" study.     

Use of spatial statistics to identify and test significance in geographic disease patterns

Spatial analysis provides a powerful method to test epidemiologic hypotheses about patterns of disease occurrence. Available techniques can be classified based on the type of data which they utilize, generally areas or points, and the primary question of interest. Three issues relevant to epidemiology are: whether a disease is clustered; whether two diseases or a disease and potential risk factor have the same distribution; and if there are specific definable relationships between the values of the same variable at different locations. Join count statistics, which relate actual and expected number of joins between areas with dissimilar values, and second order analysis, which compares the actual and expected distances between all points weighted by their values, give estimates of the magnitude and statistical significance of clustering in patterns. To test for codistribution between areal patterns, the kappa statistic evaluates the degree of pattern overlap corrected for chance. Tjosteim's statistic measures the correlation, corrected for point locations, of the ranked values. Spatial autocorrelation analysis can be used to test for specific network and distance associations between values, for the scale of a pattern, for defined complex spatial relationships or to remove spatial effects from more traditional regression analysis of other risk factors. Epidemiologists have uncovered spatial associations between diseases and risk factors using traditional methods. However, more widespread application of spatial analyses to objectively quantify the magnitude and significance of hypothesized geographical associations could offer new insights into disease questions.     

INTRAVERTEBRAL DISC HERNIATION (SCHMORL'S NODE) IN FIVE DOGS

The herniation of intervertebral disc material into the vertebral body, known as Schmorl's nodes, is a well described disease process in man. Schmorl's nodes have not until now been described in the dog. This paper describes intravertebral disc herniation in the dog based on five patients taken from a retrospective study of dogs suspected of having cauda equina syndrome. The significance of intravertebral disc herniation in the dog at this time is that they indicate a disturbance in the vertebral endplate, they present definite radiographic signs, should be considered in patients with ostecohondrosis, and remain a possibls etiology for fibrocartilaginous emboli. Back pain is a common sign in people when Schmorl's nodes were the only pathologic findings. The common signs of palpatory pain in the lumbosacral region of the dogs in this report is noted but cannot be directly correlated at this time to the intravertebral disc herniation; however, it is suspected in two of the cases.     

基于PB 和 RBF 神经网络模型的草坪质量综合评价

 依据现有的草坪质量评价指标体系,于２０１０年调查了２０个草地早熟禾品种成坪后的１１项指标,包括草坪的密度、质地、颜色、均一性、绿期、抗病性、盖度、耐践踏性、成坪速度、草坪强度以及生物量。然后,运用神经网络原理及Ｍａｔｌａｂ神经网络工具箱,以其中的１５个草地早熟禾品种成坪后的１１项指标的实地调查值作为网络输入,以专家打分作为网络输出,通过不断调整网络训练参数,使网络性能达到最优,构建了草坪质量综合评价的ＢＰ 和ＲＢＦ神经网络模型,并给出了ＢＰ和ＲＢＦ神经网络模型的分析方法及其Ｍａｔｌａｂ实现步骤。利用训练好了的网络模型,对其余的５个草地早熟禾品种的综合质量评价得分进行网络预测,结果表明,ＲＢＦ神经网络的预测误差均小于２％,而ＢＰ神经网络的预测误差均大于５％,因此,基于ＲＢＦ神经网络模型的草坪质量评价结果比ＢＰ神经网络更准确,可以用于草坪质量综合评价。与常规的加权法、层次分析法或模糊综合评判法评价草坪质量相比,基于ＲＢＦ神经网络模型的草坪质量综合评价,在一定程度上减少了评价中主观因素的影响,简化了计算步骤,为草坪质量综合评价提供了一种全新的思路。     

Relationship of trade patterns of the Danish swine industry animal movements network to potential disease spread

The movements of animals were analysed under the conceptual framework of graph theory in mathematics. The swine production related premises of Denmark were considered to constitute the nodes of a network and the links were the animal movements. In this framework, each farm will have a network of other premises to which it will be linked. A premise was a farm (breeding, rearing or slaughter pig), an abattoir or a trade market. The overall network was divided in premise specific subnets that linked the other premises from and to which animals were moved. This approach allowed us to visualise and analyse the three levels of organization related to animal movements that existed in the Danish swine production registers: the movement of animals between two premises, the premise specific networks, and the industry network. The analyses of animal movements were done using these three levels of organisation. The movements of swine were studied for the period September 30, 2002 to May 22, 2003. For daily movements of swine between two slaughter pig premises, the median number of pigs moved was 130 pigs with a maximum of 3306. For movements between a slaughter pig premise and an abattoir, the median number of pigs was 24. The largest percentage of movements was from farm to abattoir (82.5%); the median number of pigs per movement was 24 and the maximum number was 2018. For the whole period the median and maximum Euclidean distances observed in farm-to-farm movements were 22 km and 289 km respectively, while in the farm-to-abattoir movements, they were 36.2 km and 285 km. The network related to one specific premise showed that the median number of premises was mainly away from slaughter pig farms (3) or breeder farms (26) and mainly to an abattoir (1535). The assumption that animal movements can be randomly generated on the basis of farm density of the surrounding area of any farm is not correct since the patterns of animal movements have the topology of a scale-free network with a large degree of heterogeneity. This supported the opinion that the disease spread software assuming homogeneity in farm-to-farm relationship should only be used for large-scale interpretation and for epidemic preparedness. The network approach, based on graph theory, can be used efficiently to express more precisely, on a local scale (premise), the heterogeneity of animal movements. This approach, by providing network knowledge to the local veterinarian in charge of controlling disease spread, should also be evaluated as a potential tool to manage epidemics during the crisis. Geographic information systems could also be linked in the approach to produce knowledge about local transmission of disease.