[Show abstract][Hide abstract] ABSTRACT: 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.
Veterinary Research 10/2014; 45(1):110. DOI:10.1186/PREACCEPT-1387776792126309 · 2.82 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Comparisons between mass-action or "random" network models and empirical networks have produced mixed results. Here we seek to discover whether a simulated disease spread through randomly constructed networks can be coerced to model the spread in empirical networks by altering a single disease parameter-the probability of infection. A stochastic model for disease spread through herds of cattle is utilised to model the passage of an SEIR (susceptible-latent-infected-resistant) through five networks. The first network is an empirical network of recorded contacts, from four datasets available, and the other four networks are constructed from randomly distributed contacts based on increasing amounts of information from the recorded network. A numerical study on adjusting the value of the probability of infection was conducted for the four random network models. We found that relative percentage reductions in the probability of infection, between 5.6% and 39.4% in the random network models, produced results that most closely mirrored the results from the empirical contact networks. In all cases tested, to reduce the differences between the two models, required a reduction in the probability of infection in the random network.
Theoretical Population Biology 09/2014; 98. DOI:10.1016/j.tpb.2014.08.004 · 1.70 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background
The impact of non-commercial producers on disease spread via livestock movement is related to their level of interaction with other commercial actors within the industry. Although understanding these relationships is crucial in order to identify likely routes of disease incursion and transmission prior to disease detection, there has been little research in this area due to the difficulties of capturing movements of small producers with sufficient resolution. Here, we used the Scottish Livestock Electronic Identification and Traceability (ScotEID) database to describe the movement patterns of different pig production systems which may affect the risk of disease spread within the swine industry. In particular, we focused on the role of small pig producers.
Between January 2012 and May 2013, 23,169 batches of pigs were recorded moving animals between 2382 known unique premises. Although the majority of movements (61%) were to a slaughterhouse, the non-commercial and the commercial sectors of the Scottish swine industry coexist, with on- and off-movement of animals occurring relatively frequently. For instance, 13% and 4% of non-slaughter movements from professional producers were sent to a non-assured commercial producer or to a small producer, respectively; whereas 43% and 22% of movements from non-assured commercial farms were sent to a professional or a small producer, respectively. We further identified differences between producer types in several animal movement characteristics which are known to increase the risk of disease spread. Particularly, the distance travelled and the use of haulage were found to be significantly different between producers.
These results showed that commercial producers are not isolated from the non-commercial sector of the Scottish swine industry and may frequently interact, either directly or indirectly. The observed patterns in the frequency of movements, the type of producers involved, the distance travelled and the use of haulage companies provide insights into the structure of the Scottish swine industry, but also highlight different features that may increase the risk of infectious diseases spread in both Scotland and the UK. Such knowledge is critical for developing more robust biosecurity and surveillance plans and better preparing Scotland against incursions of emerging swine diseases.
BMC Veterinary Research 06/2014; 10(1):140. DOI:10.1186/1746-6148-10-140 · 1.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: 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 repeated cross-sectional surveys carried out in Scotland from 1998 to 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 previous status of farms. Pulsed-field gel electrophoresis (PFGE) profiles were further examined to ascertain whether local spread or persistence of strains could be inferred.
The presence of an E. coli O157 positive local farm (average distance: 5.96km) in the Highlands, North East and South West of Scotland, the size of farm 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 also 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.
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 exact mechanisms of transmission which should ultimately help with the design of control measures to reduce E. coli O157 from livestock-related sources.
BMC Veterinary Research 04/2014; 10(1):95. DOI:10.1186/1746-6148-10-95 · 1.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Data from 255 Scottish beef suckler herds and 189 Scottish dairy herds surveyed as part of national bovine viral diarrhoea virus (BVDV) prevalence studies from October 2006 to May 2008 were examined retrospectively to determine the relationship between serological status and key performance indicators derived from national cattle movement records. On average, calf mortality rates were 1.35 percentage points higher in seropositive beef herds and 3.05 percentage points higher in seropositive dairy herds than in negative control herds. Seropositive beef herds were also more likely to show increases in calf mortality rates and culling rates between successive years. There were no discernible effects of BVDV on the average age at first calving or calving interval for either herd type.
Accompanying questionnaire data revealed that only 27% of beef farmers and 25% of dairy farmers with seropositive herds thought their cattle were affected by BVDV, which suggests that the clinical effects of exposure may be inapparent under field conditions or masked by other causes of reproductive failure and culling. Beef farmers were significantly more likely to perceive a problem when their herd experienced acute changes in calf mortality rates, culling rates, and calving intervals between successive years. However, only 35% of these perceived positive herds were actually seropositive for BVDV. These findings emphasize both the importance of routinely screening herds to determine their true infection status and the potential for using national cattle movement records to identify herds that may be experiencing outbreaks from BVDV or other infectious diseases that impact herd performance.
The Veterinary Journal 12/2013; 198(3):631–637. DOI:10.1016/j.tvjl.2013.09.017 · 1.76 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: While demands for animal disease surveillance systems are growing, there has been little applied research that has examined the interactions between resource allocation, cost-effectiveness, and behavioral considerations of actors throughout the livestock supply chain in a surveillance system context. These interactions are important as feedbacks between surveillance decisions and disease evolution may be modulated by their contextual drivers, influencing the cost-effectiveness of a given surveillance system. This paper identifies a number of key behavioral aspects involved in animal health surveillance systems and reviews some novel methodologies for their analysis. A generic framework for analysis is discussed, with exemplar results provided to demonstrate the utility of such an approach in guiding better disease control and surveillance decisions.
PLoS ONE 11/2013; 8(11):e82019. DOI:10.1371/journal.pone.0082019 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: When facing incursion of a major livestock infectious disease, the decision to implement a vaccination programme is made at the national level. To make this decision, governments must consider whether the benefits of vaccination are sufficient to outweigh potential additional costs, including further trade restrictions that may be imposed due to the implementation of vaccination. However, little consensus exists on the factors triggering its implementation on the field. This work explores the effect of several triggers in the implementation of a reactive vaccination-to-live policy when facing epidemics of foot-and-mouth disease. In particular, we tested whether changes in the location of the incursion and the delay of implementation would affect the epidemiological benefit of such a policy in the context of Scotland. To reach this goal, we used a spatial, premises-based model that has been extensively used to investigate the effectiveness of mitigation procedures in Great Britain. The results show that the decision to vaccinate, or not, is not straightforward and strongly depends on the underlying local structure of the population-at-risk. With regards to disease incursion preparedness, simply identifying areas of highest population density may not capture all complexities that may influence the spread of disease as well as the benefit of implementing vaccination. However, if a decision to vaccinate is made, we show that delaying its implementation in the field may markedly reduce its benefit. This work provides guidelines to support policy makers in their decision to implement, or not, a vaccination-to-live policy when facing epidemics of infectious livestock disease.
PLoS ONE 10/2013; 8(10):e77616. DOI:10.1371/journal.pone.0077616 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Identifying the major sources of risk in disease transmission is key to designing effective controls. However, understanding of transmission dynamics across species boundaries is typically poor, making the design and evaluation of controls particularly challenging for zoonotic pathogens. One such global pathogen is Escherichia coli O157, which causes a serious and sometimes fatal gastrointestinal illness. Cattle are the main reservoir for E. coli O157, and vaccines for cattle now exist. However, adoption of vaccines is being delayed by conflicting responsibilities of veterinary and public health agencies, economic drivers, and because clinical trials cannot easily test interventions across species boundaries, lack of information on the public health benefits. Here, we examine transmission risk across the cattle-human species boundary and show three key results. First, supershedding of the pathogen by cattle is associated with the genetic marker stx2. Second, by quantifying the link between shedding density in cattle and human risk, we show that only the relatively rare supershedding events contribute significantly to human risk. Third, we show that this finding has profound consequences for the public health benefits of the cattle vaccine. A naïve evaluation based on efficacy in cattle would suggest a 50% reduction in risk; however, because the vaccine targets the major source of human risk, we predict a reduction in human cases of nearly 85%. By accounting for nonlinearities in transmission across the human-animal interface, we show that adoption of these vaccines by the livestock industry could prevent substantial numbers of human E. coli O157 cases.
Proceedings of the National Academy of Sciences 09/2013; 110(40). DOI:10.1073/pnas.1304978110 · 9.67 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The success of bovine viral diarrhoea virus (BVDV) eradication campaigns can be undermined by spread through local transmission pathways and poor farmer compliance with biosecurity recommendations. This work combines recent survey data with cattle movement data to explore the issues likely to impact on the success of BVDV control in Scotland. In this analysis, data from 249 beef suckler herds and 185 dairy herds in Scotland were studied retrospectively to determine the relative influence of cattle movements, local spread, and biosecurity on BVDV seropositivity. Multivariable logistic regression models revealed that cattle movement risk factors had approximately 3 times greater explanatory power than risk factors for local spread amongst beef suckler herds, but approximately the same explanatory power as risk factors for local spread amongst dairy herds. These findings are most likely related to differences in cattle husbandry practices and suggest that where financial prioritization is required, focusing on reducing movement-based risk is likely to be of greatest benefit when applied to beef suckler herds. The reported use of biosecurity measures such as purchasing cattle from BVDV accredited herds only, performing diagnostic screening at the time of sale, implementing isolation periods for purchased cattle, and installing double fencing on shared field boundaries had minimal impact on the risk of beef or dairy herds being seropositive for BVDV. Only 28% of beef farmers and 24% of dairy farmers with seropositive herds recognized that their cattle were affected by BVDV and those that did perceive a problem were no less likely to sell animals as replacement breeding stock and no more likely to implement biosecurity measures against local spread than farmers with no perceived problems. In relation to the current legislative framework for BVDV control in Scotland, these findings emphasize the importance of requiring infected herds take appropriate biosecurity measures to prevent further disease transmission and conducting adequate follow-up to ensure that biosecurity measures are being implemented correctly in the field.
Preventive Veterinary Medicine 08/2013; 112(3-4). DOI:10.1016/j.prevetmed.2013.07.017 · 2.17 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Bovine Viral Diarrhoea Virus (BVDV) is a pestivirus which infects cattle populations worldwide and is recognised as a significant source of economic loss through its impact on health and productivity. Studies investigating the molecular epidemiology of BVDV can give invaluable information about the diversity of viral strains present in a population and this, in turn, can inform control programs, drive vaccine development and determine likely infection sources. The current study investigated 104 viral isolates from forty farms across the UK. Through phylogenetic and nucleotide sequence analysis of the 5[prime]UTR and Npro regions of the isolates investigated, it was determined that BVDV 1a was the predominant sub-genotype. However, BVDV 1b, 1e and 1i were also identified and, for the first time in the UK, BVDV 1d. Through analysis of animal movement data alongside the phylogenetic analysis of these BVD isolates, it was possible to link animal movements to the viral isolates present on several premises and, for the first time, begin to elucidate the routes of viral transmission. With further work, this type of analysis would enable accurate determination and quantification of the true biosecurity risk factors associated with BVDV transmission.
Veterinary Research 06/2013; 44(1):43. DOI:10.1186/1297-9716-44-43 · 2.82 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The paper analyses the impact of a priori determinants of biosecurity behaviour of farmers in Great Britain. We use a dataset collected through a stratified telephone survey of 900 cattle and sheep farmers in Great Britain (400 in England and a further 250 in Wales and Scotland respectively) which took place between 25 March 2010 and 18 June 2010. The survey was stratified by farm type, farm size and region. To test the influence of a priori determinants on biosecurity behaviour we used a behavioural economics method, structural equation modelling (SEM) with observed and latent variables. SEM is a statistical technique for testing and estimating causal relationships amongst variables, some of which may be latent using a combination of statistical data and qualitative causal assumptions. Thirteen latent variables were identified and extracted, expressing the behaviour and the underlying determining factors. The variables were: experience, economic factors, organic certification of farm, membership in a cattle/sheep health scheme, perceived usefulness of biosecurity information sources, knowledge about biosecurity measures, perceived importance of specific biosecurity strategies, perceived effect (on farm business in the past five years) of welfare/health regulation, perceived effect of severe outbreaks of animal diseases, attitudes towards livestock biosecurity, attitudes towards animal welfare, influence on decision to apply biosecurity measures and biosecurity behaviour. The SEM model applied on the Great Britain sample has an adequate fit according to the measures of absolute, incremental and parsimonious fit. The results suggest that farmers' perceived importance of specific biosecurity strategies, organic certification of farm, knowledge about biosecurity measures, attitudes towards animal welfare, perceived usefulness of biosecurity information sources, perceived effect on business during the past five years of severe outbreaks of animal diseases, membership in a cattle/sheep health scheme, attitudes towards livestock biosecurity, influence on decision to apply biosecurity measures, experience and economic factors are significantly influencing behaviour (overall explaining 64% of the variance in behaviour). Three other models were run for the individual regions (England, Scotland and Wales). A smaller number of variables were included in each model to account for the smaller sample sizes. Results show lower but still high levels of variance explained for the individual models (about 40% for each country). The individual models' results are consistent with those of the total sample model. The results might suggest that ways to achieve behavioural change could include ensuring increased access of farmers to biosecurity information and advice sources.
Preventive Veterinary Medicine 11/2012; 108(4). DOI:10.1016/j.prevetmed.2012.11.009 · 2.17 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Bulk tank milk samples were collected from 374 dairy farms in Scotland in 2007/2008 along with questionnaire data relating to the management of the farm. Milk samples were tested for antibodies to bovine viral diarrhoea virus (BVDV) using a commercially available (Svanova) kit and percentage positivity scores calculated according to the manufacturer's guidelines. There were 220 farms that did not routinely vaccinate for bovine viral diarrhoea (BVD), and these were distributed according to the Swedish BVD eradication classes as 12.7 per cent, 22.3 per cent, 44.5 per cent and 20.5 per cent for Classes 0, 1, 2 and 3, respectively. A more sophisticated statistical method (finite mixture modelling) which does not depend on arbitrary thresholds and categories suggested a 73 per cent prevalence of herds with high mean levels of antibodies. Risk factor analysis suggested that routine vaccination for BVD, suspicion of BVD, housing of pregnant cows with calves, total number of cows and the proportion of cows that were dry were all associated with increased BVDV antibodies in bulk milk. The inclusion of BVD within the farm's health plan was associated with decreased BVDV antibodies in the bulk milk.
[Show abstract][Hide abstract] ABSTRACT: Background
Abattoir detected pathologies are of crucial importance to both pig production and food safety. Usually, more than one pathology coexist in a pig herd although it often remains unknown how these different pathologies interrelate to each other. Identification of the associations between different pathologies may facilitate an improved understanding of their underlying biological linkage, and support the veterinarians in encouraging control strategies aimed at reducing the prevalence of not just one, but two or more conditions simultaneously.
Multi-dimensional machine learning methodology was used to identify associations between ten typical pathologies in 6485 batches of slaughtered finishing pigs, assisting the comprehension of their biological association. Pathologies potentially associated with septicaemia (e.g. pericarditis, peritonitis) appear interrelated, suggesting on-going bacterial challenges by pathogens such as Haemophilus parasuis and Streptococcus suis. Furthermore, hepatic scarring appears interrelated with both milk spot livers (Ascaris suum) and bacteria-related pathologies, suggesting a potential multi-pathogen nature for this pathology.
The application of novel multi-dimensional machine learning methodology provided new insights into how typical pig pathologies are potentially interrelated at batch level. The methodology presented is a powerful exploratory tool to generate hypotheses, applicable to a wide range of studies in veterinary research.
BMC Veterinary Research 08/2012; 8(1):151. DOI:10.1186/1746-6148-8-151 · 1.78 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We present two stochastic models of the passage of an SEIR (susceptible-latent-infected-resistant) disease through herds of cattle. One model is based on a contact network constructed via continuously recorded interaction data from two herds of cattle, the other, a matching network constructed using the principles of mass-action mixing. The recorded contact data were produced by attaching proximity data loggers to two separate herds of cattle during two separate recording periods. The network constructed using the principles of mass-action mixing uses the same number of contacts as the recorded network but distributes them randomly amongst the animals. The recorded networks had a greater number of repeated contacts, lower closeness and clustering scores and greater average path length than the mass-action networks. A lower proportion of simulations of the recorded network produce any disease spread when compared to those simulations of the mass-action network and, of those that did, fewer infected animals were predicted. For all parameter values tested, within the sensitivity analysis, similar differences were found between the recorded and mass-action network models.
[Show abstract][Hide abstract] ABSTRACT: Bovine viral diarrhoea virus (BVDV) causes an economically important endemic disease (BVD) of cattle in Ireland and worldwide. Systematic eradication by detection and removal of infectious (BVDV carrier) cattle has been successful in several regions. We therefore assessed the benefits (disease losses avoided) and costs (testing and culling regime) of a potential eradication programme in Ireland. Published bio-economic models of BVDV spread in beef suckler herds and dairy herds were adapted to estimate potential benefits of eradication in Ireland. A simple model of BVDV spread in beef finisher herds was devised to estimate the benefits of eradication in this sector. A six year eradication programme consisting of 5 inter-related virological and serological testing programmes is outlined and costed. We found that the annualised benefits of BVDV eradication in Ireland exceeded the costs by a factor of 5 in the beef suckler sector and a factor of 14 in the dairy sector. Corresponding payback periods were 1.2 and 0.5 years respectively. These results highlight the significant economic impact of BVDV on the Irish cattle industry and suggest a clear economic benefit to eradication using the proposed approach. This type of cost-benefit analysis is considered an essential prerequisite prior to undertaking an eradication campaign of this magnitude.