Direct and indirect contacts between cattle farms in north-west England

Uncommon bovine viral diarrhea virus subtype 1e associated with abortions in cattle in southern Brazil

We characterized bovine viral diarrhea virus (BVDV)-related abortions in cattle and identified the species and subgenotypes in the state of Santa Catarina, southern Brazil. Our RT-PCR assay was positive for BVDV in 5 fetuses from different farms; however, 3 of the 5 fetuses were also PCR-positive for Neospora caninum. In the 5 BVDV-positive fetuses, gross lesions included fetal mummification (1), hepatomegaly (1), subcutaneous edema (1), and perirenal edema (1). Predominant histologic lesions included epicarditis and mild-to-moderate lymphoplasmacytic myocarditis (5), mild multifocal lymphoplasmacytic interlobular pneumonia (4), nephrosis associated with moderate multifocal interstitial nephritis (1), moderate multifocal lymphoplasmacytic necrotic hepatitis (1), and mild multifocal lymphoplasmacytic meningitis (1). The amplification products from the Pestivirus 5'UTR region of 4 of the 5 fetuses had 96.3-100% similarity between fetal strains and reference strains. The samples were distributed into 2 branches of the phylogenetic tree; strains UDESC:01, UDESC:02, and UDESC:05 clustered in the BVDV-1e branch, uncommon in the Americas, and strain UDESC:04 clustered in the BVDV-2b branch. The three 1e strains had 96.9-97.4% similarity.

Genomic Diversity, Antimicrobial Resistance, Plasmidome, and Virulence Profiles of Salmonella Isolated from Small Specialty Crop Farms Revealed by Whole-Genome Sequencing

Salmonella is the leading cause of death associated with foodborne illnesses in the USA. Difficulty in treating human salmonellosis is attributed to the development of antimicrobial resistance and the pathogenicity of Salmonella strains. Therefore, it is important to study the genetic landscape of Salmonella, such as the diversity, plasmids, and presence antimicrobial resistance genes (AMRs) and virulence genes. To this end, we isolated Salmonella from environmental samples from small specialty crop farms (SSCFs) in Northeast Ohio from 2016 to 2021; 80 Salmonella isolates from 29 Salmonella-positive samples were subjected to whole-genome sequencing (WGS). In silico serotyping revealed the presence of 15 serotypes. AMR genes were detected in 15% of the samples, with 75% exhibiting phenotypic and genotypic multidrug resistance (MDR). Plasmid analysis demonstrated the presence of nine different types of plasmids, and 75% of AMR genes were located on plasmids. Interestingly, five Salmonella Newport isolates and one Salmonella Dublin isolate carried the ACSSuT gene cassette on a plasmid, which confers resistance to ampicillin, chloramphenicol, streptomycin, sulfonamide, and tetracycline. Overall, our results show that SSCFs are a potential reservoir of Salmonella with MDR genes. Thus, regular monitoring is needed to prevent the transmission of MDR Salmonella from SSCFs to humans.

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

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

Direct and indirect pathways for the spread of African swine fever and other porcine infectious diseases: An application of the mental models approach

In this study, we investigated the occurrence of direct and indirect infectious disease transmission pathways among pig farms in Switzerland, as well as their specific relevance for the spread of African swine fever, porcine reproductive and respiratory syndrome (PRRS), and enzootic pneumonia. Data were collected using an adapted mental models approach, involving initial interviews with experts in the field of pig health and logistics, semi-structured interviews with pig farmers, and a final expert workshop, during which all identified pathways were graded by their predicted frequency of occurrence, their likelihood of spread of the three diseases of interest, and their overall relevance considering both parameters. As many as 24 disease pathways were identified in four areas: pig trade, farmer encounters, external collaborators, and environmental or other pathways. Two thirds of the pathways were expected to occur with moderate-to-high frequency. While both direct and indirect pig trade transmission routes were highly relevant for the spread of the three pathogens, pathways from the remaining areas were especially important for PRRS due to higher spread potential via aerosols and fomites. In addition, we identified factors modifying the relevance of disease pathways, such as farm production type and affiliation with trader companies. During the interviews, we found varying levels of risk perception among farmers concerning some of the pathways, which affected adherence to biosecurity measures and were often linked to the degree of trust that farmers had towards their colleagues and external collaborators. Our findings highlight the importance of integrating indirect disease pathways into existing surveillance and control strategies and in disease modelling efforts. We also propose that biosecurity training aimed at professionals and risk communication campaigns targeting farmers should be considered to mitigate the risk of disease spread through the identified pathways.

Quantifying Land Fragmentation in Northern Irish Cattle Enterprises

Farmland fragmentation is considered to be a defining feature of Northern Ireland’s (NI) agricultural landscape, influencing agricultural efficiency, productivity, and the spread of livestock diseases. Despite this, the full extent of farmland fragmentation in cattle farms in NI is not well understood, and little is known of how farmland fragmentation either influences, or is influenced by, different animal production types. Here, we describe and quantify farmland fragmentation in cattle farms for all of NI, using GIS processing of land parcel data to associate individual parcels with data on the cattle business associated with the land. We found that 35% of farms consisted of five or more fragments, with dairy farms associated with greater levels of farmland fragmentation, fragment dispersal and contact with contiguous neighbours compared to other production types. The elevated levels of farmland fragmentation in dairy production compared to non-dairy, may be associated with the recent expansion of dairy farms by land acquisition, following the abolition of the milk quota system in 2015. The comparatively high levels of farmland fragmentation observed in NI cattle farms may also have important implications for agricultural productivity and epidemiology alike. Whilst highly connected pastures could facilitate the dissemination of disease, highly fragmented land could also hamper productivity via diseconomies of scale, such as preventing the increase of herd sizes or additionally, adding to farm costs by increasing the complexity of herd management.

Investigating Farm Fragmentation as a Risk Factor for Bovine Tuberculosis in Cattle Herds: A Matched Case-Control Study from Northern Ireland

Bovine tuberculosis remains a challenging endemic pathogen of cattle in many parts of the globe. Spatial clustering of Mycoacterium bovis molecular types in cattle suggests that local factors are the primary drivers of spread. Northern Ireland’s agricultural landscape is comprised of highly fragmented farms, distributed across spatially discontinuous land parcels, and these highly fragmented farms are thought to facilitate localised spread. We conducted a matched case control study to quantify the risks of bovine tuberculosis breakdown with farm area, farm fragmentation, fragment dispersal, and contact with neighbouring herds. Whilst our results show small but significant increases in breakdown risk associated with each factor, these relationships were strongly confounded with the number of contiguous neighbours with bovine tuberculosis. Our key finding was that every infected neighbour led to an increase in the odds of breakdown by 40% to 50%, and that highly fragmented farms were almost twice as likely to have a bTB positive neighbour compared to nonfragmented farms. Our results suggest that after controlling for herd size, herd type, spatial and temporal factors, farm fragmentation increasingly exposes herds to infection originating from first-order spatial neighbours. Given Northern Ireland’s particularly fragmented landscape, and reliance on short-term leases, our data support the hypothesis that between-herd contiguous spread is a particularly important component of the region’s bovine tuberculosis disease system.

Unravelling direct and indirect contact patterns between duck farms in France and their association with the 2016-2017 epidemic of Highly Pathogenic Avian Influenza (H5N8)

Live animal movements generate direct contacts (via the exchange of live animals) and indirect contacts (via the transit of transport vehicles) between farms, which can contribute to the spread of pathogens. However, most analyses focus solely on direct contacts and can therefore underestimate the contribution of live animal movements in the spread of infectious diseases. Here, we used French live duck movement data (2016-2018) from one of the largest transport companies to compare direct and indirect contact patterns between duck farms and evaluate how these patterns were associated with the French 2016-2017 epidemic of highly pathogenic avian influenza H5N8. A total number of 614 farms were included in the study, and two directed networks were generated: the animal introduction network (exchange of live ducks) and the transit network (transit of transport vehicles). Following descriptive analyses, these two networks were scrutinized in relation to farm infection status during the epidemic. Results showed that farms were substantially more connected in the transit network than in the animal introduction network and that the transit of transport vehicles generated more opportunities for transmission than the exchange of live animals. We also showed that animal introduction and transit networks' statistics decreased substantially during the epidemic (January-March 2017) compared to non-epidemic periods (January-March 2016 and January-March 2018). We estimated a probability of 33.3 % that a farm exposed to the infection through either of the two live duck movement networks (i.e. that was in direct or indirect contact with a farm that was reported as infected in the following seven days) becomes infected within seven days after the contact. However, we also demonstrated that the level of exposure of farms by these two contact patterns was low, leading only to a handful of transmission events through these routes. As a consequence, we showed that live animal movement patterns are efficient transmission routes for HPAI but have been efficiently reduced to limit the spread during the French 2020-2021 epidemic. These results underpin the relevance of studying indirect contacts resulting from the movement of animals to understand their transmission potential and the importance of accounting for both routes when designing disease control strategies.

Spatial and network analysis of U.S. livestock movements based on Interstate Certificates of Veterinary Inspection

Livestock movements are a common pathway for the spread infectious diseases in a population. An understanding of livestock movement patterns is needed to understand national transmission risks of highly infectious diseases during epidemics. Social Network Analysis (SNA) is an approach that helps to describe the relationships among individuals and the implications of those relationships. We used SNA to describe the contact structure of livestock movements throughout the contiguous U.S. from April 1^st, 2015 to March 31^st, 2016. We describe 4 network types: beef cattle, dairy cattle, swine, and small ruminant. Livestock movement data were sourced from Interstate Certificates of Veterinary Inspection (ICVI) while county-level farm demographic data were from the National Agricultural Statistics Service (NASS). In the described networks, nodes are represented by counties and arcs by shipments between nodes; the networks were weighted based on the number of shipments between nodes. For the analyses, movement data were aggregated at the county level and on an annual basis. Measures of centrality and cohesiveness were computed and identification of trade-communities in all networks was conducted. During the study period, a total of 219,042 movements were recorded and beef cattle movements accounted for 63 % of all movements. At least 70 % of U.S. counties were present in each of the networks, but the density of arcs was less than 2% in all networks. In the beef cattle network, counties with high out-degree were strongly correlated (0.8) with the number of beef cows per county while for the dairy cattle network a strong correlation (>0.86) was found with the number of dairy cattle per km² at the county level. All networks were found to have between 4 and 6 large communities (50 counties or more per community), and were geographically clustered except for the communities in the small ruminant network. Outputs reported in these analyses can help to understand the structure of the contact networks for beef cattle, dairy cattle, swine, and small ruminants. They may also be used in conjunction with simulation modeling to evaluate spread of highly infectious disease such as foot-and-mouth disease at the national level and to evaluate the application of intervention strategies.

Quantitative risk assessment of introduction of BVDV and BoHV-1 through indirect contacts based on implemented biosecurity measures in dairy farms of Spain

A stochastic quantitative risk assessment model was developed to estimate the annual probability of introduction of bovine viral diarrhea virus (BVDV) and bovine herpesvirus 1 (BoHV-1) on 127 dairy farms through indirect contacts. Vehicles transporting calves, cattle to slaughterhouse, dead animals, and mixture of feed, as well as visits by veterinarians and hoof trimmers, farm workers and contacts with neighbors were considered in the model. Data from biosecurity questionnaires of each farm, scientific literature and expert opinion from field veterinarians, animal vehicle drivers, hoof trimmers and personnel from rendering transport companies were used to estimate values for input parameters. Results showed that the annual probability of introducing BVDV or BoHV-1 through indirect contacts was very heterogeneous. The overall distribution of median values for each farm ranged from 0.5 to 14.6% and from 1.0 to 24.9% for BVDV and BoHV-1, respectively. The model identified that providing protective clothing and boots to visits, not allowing the animal vehicle driver to come into contact with animals present on the farm and ensuring that calf vehicles arrived empty, were the measures with the highest impact on the probability of infection for most farms. This model could be a useful tool to show the impact of the measures to farmers and veterinarians, thus increasing their awareness on biosecurity. In addition, it could support decision making on which measures should be prioritized in dairy cattle herds to reduce the probability of introduction of diseases.

Using network analysis to identify seasonal patterns and key nodes for risk-based surveillance of pig diseases in Italy

The description of the pattern of livestock movements between herds provides essential information for both improving risk-based surveillance and to understand the likely spread of infectious diseases. This study provides a description of the temporal pattern of pig movements recorded in Italy on a 4-year period (2013-2016). Data, provided by the National Livestock registry, were described by social network analysis and the application of a walk-trap algorithm for community detection. Our results show a highly populated community located in Northern Italy, which is the focal point of the Italian industrial pig production and as a general pattern an overall decline of medium and backyard farms and an increase in the number of large farms, in agreement with the trend observed by other EU pig-producing countries. A seasonal pattern of all the parameters evaluated, including the number of active nodes in both the intensive and smaller production systems, emerged: that is characterized by a higher number of movements in spring and autumn, linked with the breeding and production cycle as pigs moved from the growing to the finishing phase and with periods of increased slaughtering at Christmas and Easter. The same pattern was found when restricting the analysis to imported pig batches. Outbreaks occurring during these periods would have a greater impact on the spread of infectious diseases; therefore, targeted surveillance may be appropriate. Finally, potential super-spreader nodes have been identified and represent 0.47% of the total number of pig holdings (n = 477). Those nodes are present during the whole study period with a similar ranking in their potential of being super-spreaders. Most of them were in Northern Italy, but super-spreaders with high mean out-degree centrality were also located in other Regions. Seasonality, communities and super-spreaders should be considered when planning surveillance activity and when applying disease control strategies.

Quantifying intraherd cattle movement metrics: Implications for disease transmission risk

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

Impact of truck contamination and information sharing on foot-and-mouth disease spreading in beef cattle production systems

As cattle movement data in the United States are scarce due to the absence of mandatory traceability programs, previous epidemic models for U.S. cattle production systems heavily rely on contact rates estimated based on expert opinions and survey data. These models are often based on static networks and ignore the sequence of movement, possibly overestimating the epidemic sizes. In this research, we adapt and employ an agent-based model that simulates beef cattle production and transportation in southwest Kansas to analyze the between-premises transmission of a highly contagious disease, foot-and-mouth disease. First, we assess the impact of truck contamination on the disease transmission with the truck agent following an independent clean-infected-clean cycle. Second, we add an information-sharing functionality such that producers/packers can trace back and forward their trade records to inform their trade partners during outbreaks. Scenario analysis results show that including indirect contact routes between premises via truck movements can significantly increase the amplitude of disease spread, compared with equivalent scenarios that only consider animal movement. Mitigation strategies informed by information sharing can effectively mitigate epidemics, highlighting the benefit of promoting information sharing in the cattle industry. In addition, we identify salient characteristics that must be considered when designing an information-sharing strategy, including the number of days to trace back and forward in the trade records and the role of different cattle supply chain stakeholders. Sensitivity analysis results show that epidemic sizes are sensitive to variations in parameters of the contamination period for a truck or a loading/unloading area of premises, and indirect contact transmission probability and future studies can focus on a more accurate estimation of these parameters.

Grazing cattle exposure to neighbouring herds and badgers in relation to bovine tuberculosis risk

Bovine tuberculosis (bTB) can be spread between and among cattle and wildlife hosts e.g. European badger (Meles meles). The majority of cattle in the UK and Ireland are grazed during the summer, potentially exposing them to Mycobacterium bovis. 18 farms were surveyed (39% dairy, 61% beef; fields n = 697) for one grazing season (May-November 2016, n = 148,461 field days) to quantify the co-occurrence of cattle with badger setts and latrines and adjacency to neighbouring cattle herds. 3% (n = 24) of the fields had a badger sett or latrine recorded, dairy cattle were significantly more likely to co-occur with badger setts and latrines than beef cattle. Most farms (89%) grazed cattle adjacent to a neighbouring herd, which accounted for 18% of the grazing season. Potential exposure to neighbouring herds did not differ between production systems but did vary between life stages. A significant positive association between the proportion of time cattle spent grazing fields with setts present and the historic 1-, 3- and 5- year bTB status (p = 0.007, p = 0.013 and p = 0.013 respectively) was found. However, when cattle were grazed in fields with latrines, a significant negative association was found between the proportion of time cattle spent grazing fields with latrines present and the historic 3- and 5- year bTB status (p = 0.033 and p = 0.012 respectively). Historic bTB status and percentage of days spent beside a neighbouring herd was unrelated. Idiosyncrasies at farm-level and between risk factors indicated that individual farm assessments would be beneficial to understand potential exposure risk.

Characterization of potential superspreader farms for bovine tuberculosis: A review

Background

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

Objectives and Methods

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

Results

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

Conclusions

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

Multilayer and Multiplex Networks: An Introduction to Their Use in Veterinary Epidemiology

Contact network analysis has become a vital tool for conceptualizing the spread of pathogens in animal populations and is particularly useful for understanding the implications of heterogeneity in contact patterns for transmission. However, the transmission of most pathogens cannot be simplified to a single mode of transmission and, thus, a single definition of contact. In addition, host-pathogen interactions occur in a community context, with many pathogens infecting multiple host species and most hosts being infected by multiple pathogens. Multilayer networks provide a formal framework for researching host-pathogen systems in which multiple types of transmission-relevant interactions, defined as network layers, can be analyzed jointly. Here, we provide an overview of multilayer network analysis and review applications of this novel method to epidemiological research questions. We then demonstrate the use of this technique to analyze heterogeneity in direct and indirect contact patterns amongst swine farms in the United States. When contact among nodes can be defined in multiple ways, a multilayer approach can advance our ability to use networks in epidemiological research by providing an improved approach for defining epidemiologically relevant groups of interacting nodes and changing the way we identify epidemiologically important individuals such as superspreaders.

Illustration of Different Disease Transmission Routes in a Pig Trade Network by Monopartite and Bipartite Representation

Simple Summary

Besides direct animal movements between farms; indirect transmission routes of pathogens can have an immense impact on network structure and disease spread in animal trade networks. This study integrated these indirect transmission routes between farms via transport companies or feed supply as bipartite networks; which were compared to the monopartite animal movements network representing the direct transmission route. Both bipartite networks were projected on farm level to enable a comparison to the monopartite network. The number of edges increased immensely from the monopartite animal movements network to both projected networks. Thus, farms can be highly connected over indirect connections, although they are not directly trading animals. The ranking of the animals according to their centrality parameters, indicating their importance for the network, showed moderate correlations only between the animal movements and the transportation network. The epidemiological models based on the different network representations revealed significantly more infected farms for the networks including indirect transmission routes compared to the direct animal movements. Indirect transmission routes had an immense impact on the outcome of centrality parameters, as well as on the spreading process within the network. This knowledge is needed to understand disease spread and to establish reliable prevention and control measurements.

Abstract

Besides the direct transport of animals, also indirect transmission routes, e.g., contact via contaminated vehicles, have to be considered. In this study, the transmission routes of a German pig trade network were illustrated as a monopartite animal movements network and two bipartite networks including information of the transport company and the feed producer which were projected on farm level (n = 866) to enable a comparison. The networks were investigated with the help of network analysis and formed the basis for epidemiological models to evaluate the impact of different transmission routes on network structure as well as on potential epidemic sizes. The number of edges increased immensely from the monopartite animal movements network to both projected networks. The median centrality parameters revealed clear differences between the three representations. Furthermore, moderate correlation coefficients ranging from 0.55 to 0.68 between the centrality values of the animal movements network and the projected transportation network were obtained. The epidemiological models revealed significantly more infected farms for both projected networks (70% to 100%) compared to the animal movements network (1%). The inclusion of indirect transmission routes had an immense impact on the outcome of centrality parameters as well as on the results of the epidemiological models.

Seroprevalences of multi-pathogen and description of farm movement in pigs in two provinces in Vietnam

Background

In Vietnam, lack of animal health information is considered a major challenge for pig production. The main objective of this study was to assess the seroprevalences of five pathogens [porcine circovirus type 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSV), mycoplasma hyopneumoniae (M. hyo), Japanese encephalitis virus (JEV) and leptospirosis] and to better characterize the farm movements through a survey.

Results

A total of 600 samples were collected from 120 farms from Bac Giang and Nghe An. Among unvaccinated herds, the highest seroprevalence was found for JE with 73.81% (95% CI: 68.39–78.74) in Bac Giang and 53.51% (95% CI 47.68–59.27) in Nghe An. Seroprevalences for PCV2 and M.hyo were 49.43% (95% CI: 45.06–53.80) and 46.06% (95% CI: 41.48–50.69) among unvaccinated animals. Accumulative co-infections for JE (86.25%) showed the highest level followed by M. hyo (66.25%) and PCV2 (62.50%). Three co-infections with JE had the highest positive rate (28.75%) followed by four co-infections (25.0%). Medium farms had relatively higher herd prevalences for all pathogens, except from leptospirosis. Overall, farmers exported/imported their pigs at the most 1–2 times every 6 months. Some respondents (5% for exportation and 20% for importation) had moved pigs more than 6 times over the last 6 months.

Conclusions

Our study provided another pool of evidence that showed that PCV2, PRRS and H. hyo are endemic in pigs in Vietnam. Given the economic impacts of these pathogens elsewhere, the findings confirm the need for studies to evaluate the association between antibody response and clinical relevance as well as to assess the economic impact of co-infections at farm level. We also found that high seroprevalences of JE and leptospirosis were detected in pigs. From a pubic health point of view, it is crucial to raise public awareness especially for high risk occupations (mainly pig farm workers).

Pig trade networks through live pig markets in Guangdong Province, China

This study used social network analysis to investigate the indirect contact network between counties through the movement of live pigs through four wholesale live pig markets in Guangdong Province, China. All 14,118 trade records for January and June 2016 were collected from the markets and the patterns of pig trade in these markets analysed. Maps were developed to show the movement pathways. Evaluating the network between source counties was the primary objective of this study. A 1‐mode network was developed. Characteristics of the trading network were explored, and the degree, betweenness and closeness were calculated for each source county. Models were developed to compare the impacts of different disease control strategies on the potential magnitude of an epidemic spreading through this network. The results show that pigs from 151 counties were delivered to the four wholesale live pig markets in January and/or June 2016. More batches (truckloads of pigs sourced from one or more piggeries) were traded in these markets in January (8,001) than in June 2016 (6,117). The pigs were predominantly sourced from counties inside Guangdong Province (90%), along with counties in Hunan, Guangxi, Jiangxi, Fujian and Henan provinces. The major source counties (46 in total) contributed 94% of the total batches during the two‐month study period. Pigs were sourced from piggeries located 10 to 1,417 km from the markets. The distribution of the nodes' degrees in both January and June indicates a free‐scale network property, and the network in January had a higher clustering coefficient (0.54 vs. 0.39) and a shorter average pathway length (1.91 vs. 2.06) than that in June. The most connected counties of the network were in the central, northern and western regions of Guangdong Province. Compared with randomly removing counties from the network, eliminating counties with higher betweenness, degree or closeness resulted in a greater reduction of the magnitude of a potential epidemic. The findings of this study can be used to inform targeted control interventions for disease spread through this live pig market trade network in south China.

When resolution does matter: Modelling indirect contacts in dairy farms at different levels of detail

Animal exchanges are considered the major pathway for between-farm transmission of many livestock infectious diseases. Yet, vehicles and operators visiting several farms during routine activities can also contribute to disease spread. Indeed, if contaminated, they can act as mechanical vectors of fomites, generating indirect contacts between visited farms. While data on animal exchanges is often available in national databases, information about the daily itineraries of trucks and operators is rare because difficult to obtain. Thus, some unavoidable approximations have been frequently introduced in the description of indirect contacts in epidemic models. Here, we showed that the level of detail in such description can significantly affect the predictions on disease dynamics. Our analyses focused on the potential spread of a disease in a dairy farm system subject of a comprehensive data collection campaign on calf transportations. We developed two temporal multilayer networks to model between-farm contacts generated by either animal exchanges (direct contacts) and connections operated by trucks moving calves (indirect contacts). The complete model used the full knowledge of the daily trucks' itineraries, while the partial informed one used only a subset of such available information. To account for various conditions of pathogen survival ability and effectiveness of cleaning operations, we performed a sensitivity analysis on trucks' contamination period. An accurate description of indirect contacts was crucial both to correctly predict the final size of epidemics and to identify the seed farms responsible for generating the most severe outbreaks. The importance of detailed information emerged even more clearly in the case of short contamination periods. Our conclusions could be extended to between-farm contacts generated by other vehicles and operators. Overcoming these information gaps would be decisive for a deeper understanding of epidemic spread in livestock and to develop effective control plans.

Biosecurity practices in Belgian veal calf farming: Level of implementation, attitudes, strengths, weaknesses and constraints

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Biosecurity awareness among veal farmers was very low.

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On average, veal farms were filled in 11.4 days.

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On average, 124 calves originated from 100 farms of origin.

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No difference in biosecurity level could be found between different veal companies.

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Fundamental changes are needed to improve biosecurity regarding introduction of animals.

The shift from cure toward prevention in veterinary medicine involves the implementation of biosecurity. In cattle farming, the application of biosecurity measures has been described to a limited degree, yet no data on biosecurity on veal farms is available. A high degree of commingling of veal calves from multiple farms causes frequent disease outbreaks, and thereby high antimicrobial usage and increased risk of antimicrobial resistance. Therefore, this study aimed to describe the current implementation of biosecurity on veal farms in Belgium. To this extent, a list of the most important calf diseases (n = 34) was created, and risk factors and related biosecurity measures for these diseases were determined and included in a questionnaire. Herd visits and face-to-face interviews were conducted on 20 randomly selected veal farms, comprising 8.3% of the target population. A categorical principal component and clustering analysis were performed to determine the influence of the veal companies on the farms’ biosecurity level. Awareness of biosecurity was very low among the farmers. All farms used an “all-in, all-out” production system with calves originating from multiple farms without quarantine. On average, farms were filled in 11.4 days (range 2–52). The degree of commingling for these farms was 1.24, meaning that, on average, 124 calves originated from 100 farms. Veterinarians wore farm-specific boots on eight farms (40%) and farm-specific clothes on six farms (30%), while technical advisors wore farm-specific boots on six farms (30%) and farm-specific clothes on four farms (20%). Disinfection footbaths were only used in five farms (25%) despite being present in all farms in the sample. Concerning internal biosecurity, none of the farmers isolated sick animals; only one farmer (5%) had a physically separated hospital pen, and only 11 farmers (55%) both cleaned and disinfected the stables after each production cycle. In most farms, animals were of comparable age. Healthy calves generally remained in the same compartment during the entire production cycle, limiting the risks associated with the movement of animals. No influence of the integrations on the biosecurity level could be determined. It can be concluded that a few biosecurity measures, such as “‘all-in, all-out” and compartmentation, are implemented relatively well, while other measures, such as good cleaning and disinfection and proper entrance measures for visitors and personnel can easily be improved. The improvement of measures regarding the introduction of animals of different origins will require more fundamental changes in the veal industry.

Indirect interactions influence contact network structure and diffusion dynamics

Interaction patterns at the individual level influence the behaviour of diffusion over contact networks. Most of the current diffusion models only consider direct interactions, capable of transferring infectious items among individuals, to build transmission networks of diffusion. However, delayed indirect interactions, where a susceptible individual interacts with infectious items after the infected individual has left the interaction space, can also cause transmission events. We define a diffusion model called the same place different time transmission (SPDT)-based diffusion that considers transmission links for these indirect interactions. Our SPDT model changes the network dynamics where the connectivity among individuals varies with the decay rates of link infectivity. We investigate SPDT diffusion behaviours by simulating airborne disease spreading on data-driven contact networks. The SPDT model significantly increases diffusion dynamics with a high rate of disease transmission. By making the underlying connectivity denser and stronger due to the inclusion of indirect transmissions, SPDT models are more realistic than same place same time transmission (SPST)-based models for the study of various airborne disease outbreaks. Importantly, we also find that the diffusion dynamics including indirect links are not reproducible by the current SPST models based on direct links, even if both SPDT and SPST networks assume the same underlying connectivity. This is because the transmission dynamics of indirect links are different from those of direct links. These outcomes highlight the importance of the indirect links for predicting outbreaks of airborne diseases.

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.

Combining Salmonella Dublin genome information and contact-tracing to substantiate a new approach for improved detection of infectious transmission routes in cattle populations

This study presents a new method for detection of between-herd livestock movements to facilitate disease tracing and more accurately describe network behaviour of relevance for spread of infectious diseases, including within-livestock business risk-carrying contacts that are not necessarily recorded anywhere. The study introduces and substantiates the concept of grouping livestock herds into business-units based on ownership and location in the tracing analysis of animal movement-based contact networks. To test the utility of this approach, whole core genome sequencing of 196 Salmonella Dublin isolates stored from previous surveillance and project activities was combined with information on cattle movements recorded in the Danish Cattle Database between 1997 and 2017. The aim was to investigate alternative explanations for S. Dublin circulation in groups of herds connected by ownership, but without complete records of livestock movements. The EpiContactTrace R-package was used to trace the contact networks between businesses and compare the network characteristics of businesses sharing strains of S. Dublin with different levels of genetic relatedness. The ownership-only definition proved to be an unreliable grouping approach for large businesses, which could have internal distances larger than 250 km and therefore do not represent useful epidemiological units. Therefore, the grouping was refined using spatial analysis. More than 90% of final business units formed were composed of one single cattle property, whereas multi-property businesses could reach up to eight properties in a given year, with up to 15 cattle herds having been part of the same business through the study period. Results showed markedly higher probabilities of introduction of infectious animals between proposed businesses from which the same clone of S. Dublin had been isolated, when compared to businesses with non-related strains, thus substantiating the business-unit as an important epidemiological feature to consider in contact network analysis and tracing of infection routes. However, this approach may overestimate real-life contacts between cattle properties and putatively overestimate the degree of risk-contacts within each business, since it is based solely on information about property ownership and location. This does not consider administrative and individual farmers behaviours that essentially keep two properties separated. Despite this, we conclude that defining epidemiological units based on businesses is a promising approach for future disease tracing tasks.

Deterministic and stochastic analysis of an eco-epidemiological model

Chronic wasting disease (CWD) is a contagious prion disease among the deer family that has the potential to disrupt the ecosystems where deer occur in abundance. To understand the dynamics of this emerging infectious disease, we consider a simple eco-epidemic model where the host population is infected by CWD. Boundedness of the system is established. The structure of equilibria and their linearized stability are investigated. The persistence condition is discussed. By constructing a suitable Lyapunov function, we discuss the global stability of the endemic equilibrium. Local bifurcation (transcritical) around the boundary equilibria is developed. Sufficient conditions for the existence of Hopf-bifurcation are derived. Further, we have also introduced white type of noise into the system to investigate stochastic stability. This suggests that the deterministic model is robust with respect to stochastic perturbation. Some numerical simulations are performed to validate our results.

Pig movements in France: Designing network models fitting the transmission route of pathogens

Pathogen spread between farms results from interaction between the epidemiological characteristics of infectious agents, such as transmission route, and the contact structure between holdings. The objective of our study was to design network models of pig movements matching with epidemiological features of pathogens. Our first model represents the transmission of infectious diseases between farms only through the introduction of animals to holdings (Animal Introduction Model AIM), whereas the second one also accounts for pathogen spread through intermediate transit of trucks through farms even without any animal unloading (i.e. indirect transmission–Transit Model TM). To take the pyramidal organisation of pig production into consideration, these networks were studied at three different scales: the whole network and two subnetworks containing only breeding or production farms. The two models were applied to pig movement data recorded in France from June 2012 to December 2014. For each type of model, we calculated network descriptive statistics, looked for weakly/strongly connected components (WCCs/SCCs) and communities, and analysed temporal patterns. Whatever the model, the network exhibited scale-free and small-world topologies. Differences in centrality values between the two models showed that nucleus, multiplication and post-weaning farms played a key role in the spread of diseases transmitted exclusively by the introduction of infected animals, whereas farrowing and farrow-to-finish herds appeared more vulnerable to the introduction of infectious diseases through indirect contacts. The second network was less fragmented than the first one, a giant SCC being detected. The topology of network communities also varied with modelling assumptions: in the first approach, a huge geographically dispersed community was found, whereas the second model highlighted several small geographically clustered communities. These results underline the relevance of developing network models corresponding to pathogen features (e.g. their transmission route), and the need to target specific types of holdings/areas for surveillance depending on the epidemiological context.

Associations between biosecurity practices and bovine digital dermatitis in Danish dairy herds

The relationship between biosecurity and digital dermatitis (DD) was evaluated in 8,269 cows from a convenience sample of 39 freestall dairy herds. The hypothesis was that poor implementation of biosecurity was associated with higher within-herd prevalence of DD. All lactating cows were scored as negative or positive for DD at the hind legs during milking in the milking parlor. Information about biosecurity was obtained through questionnaires addressed to farmers, on-farm observations, and information from the Danish Cattle Database (www.seges.dk). These assessment tools covered potential infection sources of DD pathogens to susceptible cows (e.g., via animals, humans, manure, vehicles, equipment, and facilities). External and internal biosecurity measures were explanatory variables in 2 separate logistic regression models, whereas within-herd DD prevalence was the outcome. Overall DD prevalence among cows and herds were 24 and 97%, respectively; the within-herd DD prevalence ranged from 0 to 56%. Poor external biosecurity measures associated with higher prevalence of DD were recent animal purchase, access to pasture, lack of boots available for visitors, farm staff working at other dairy farms as well, hoof trimming without a professional attending, and animal transporters having access to cattle area. For internal biosecurity, higher DD prevalence were associated with infrequent hoof bathing, manure scraping less than 8 times a day, manure removal direction from cows to heifers, animal pens' exit without water hoses, manure-handling vehicle used in other activities, and water troughs contaminated with manure. These findings showed that improvements on biosecurity may be beneficial for controlling DD in dairy herds. The study is relevant for farmers facing problems with DD, as well as hoof trimmers, advisors, and veterinarians, who can use the results for optimized recommendations regarding biosecurity in relation to DD. Furthermore, our results might be considered by future studies investigating DD pathogen reservoirs and transmission routes.

Modelling farm-to-farm disease transmission through personnel movements: from visits to contacts, and back

Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases.

The Potential Role of Direct and Indirect Contacts on Infection Spread in Dairy Farm Networks

Animals' exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics.

Review: welfare of dairy cows in continuously housed and pasture-based production systems

There is increasing interest in the use of continuous housing systems for dairy cows, with various reasons put forward to advocate such systems. However, the welfare of dairy cows is typically perceived to be better within pasture-based systems, although such judgements are often not scientifically based. The aim of this review was to interrogate the existing scientific literature to compare the welfare, including health, of dairy cows in continuously housed and pasture-based systems. Although summarising existing work, knowledge gaps and directions for future research are also identified. The scope of the review is broad, examining relevant topics under three main headings; health, behaviour and physiology. Regarding health, cows on pasture-based systems had lower levels of lameness, hoof pathologies, hock lesions, mastitis, uterine disease and mortality compared with cows on continuously housed systems. Pasture access also had benefits for dairy cow behaviour, in terms of grazing, improved lying/resting times and lower levels of aggression. Moreover, when given the choice between pasture and indoor housing, cows showed an overall preference for pasture, particularly at night. However, the review highlighted the need for a deeper understanding of cow preference and behaviour. Potential areas for concern within pasture-based systems included physiological indicators of more severe negative energy balance, and in some situations, the potential for compromised welfare with exposure to unpredictable weather conditions. In summary, the results from this review highlight that there remain considerable animal welfare benefits from incorporating pasture access into dairy production systems.

Patterns of between-farm contacts via professionals in Sweden

Background

Infectious diseases of livestock have negative consequences for animal production as well as animal health and welfare and can be transmitted between farms via direct (live animal movements) as well as indirect (via physical vectors such as, people, transport vehicles and fomites) contacts. The objective of the study was to examine the travel patterns of professionals visiting Swedish farms (veterinarians, milk tanker drivers, artificial inseminators, maintenance technicians and livestock hauliers). This was done by obtaining records of the farms visited by a sample of professionals in the above categories in one week in January, one week in April, one week in July and one week in October in the Swedish counties Västerbotten, Södermanland, Västergötland and Skåne.

Results

There were twelve participating organisations, and data was provided for one to three individuals/vehicles/veterinary practices per professional category and per geographic region (except for dairy service technicians and livestock hauliers who did not provide data from all regions). There was a trend towards larger areas covered and smaller number of farms visited per week in the north, but exceptions occurred and there were regional variations. Generally, the greatest areas were travelled by milk tankers and livestock hauliers, and the profession travelling over the smallest areas tended to be the veterinarians. Milk tankers visited most farms per week, one milk tanker could visit between 23 and 90 farms per week and travel over areas between 717 km² and 23,512 km² per week.

Conclusions

Valuable insight into the travel patterns of Swedish professionals has emerged although the implications of the study largely concern highly infectious diseases. Movement of live animals pose the greatest risk for the spread of infectious animal diseases; however indirect contacts are important for many diseases. The results of this study indicate that in Sweden a highly contagious disease might spread over a large area in the time span of one incubation period, which ought to be kept in mind in case of an outbreak and in outbreak investigations. The difficulties in contacting some professionals visiting farms could be a problem in an outbreak situation.

Description and analysis of the poultry trading network in the Lake Alaotra region, Madagascar: implications for the surveillance and control of Newcastle disease

Madagascar's 36.5-million-head poultry industry holds a foremost place in its economy and the livelihood of its people. Unfortunately, regular Newcastle disease outbreaks associated with high mortality causes high losses for smallholders and threatens their livelihood. Therefore, Madagascar is seeking concrete, achievable and sustainable methods for the surveillance and the control of Newcastle disease. In this paper, we present and analyze the results of a field study conducted in Madagascar between December 2009 and December 2010. The study area was the Lac Alaotra region, a landlocked area in the north-eastern part of the country's center. Poultry trading is suspected of playing a major role in the spread of avian diseases, especially in developing countries characterized by many live-bird markets and middlemen. Therefore, the goals of our study were to: (i) describe and analyze smallholders' poultry trading network in the Lake Alaotra region using social network analysis; (ii) assess the role of the network in the spread of Newcastle disease; and (iii) propose the implementation of a targeted disease surveillance based on the characteristics of the poultry trading network. We focused our field study on the harvesting of two data sets. The first is a complete description of the poultry trading network in the landlocked area of Lac Alaotra, including a description of the poultry movements between groups of villages. The second set of data measures the occurrence of outbreaks in the same area by combining a participatory approach with an event-based surveillance method. These data were used to determine the attributes of the network, and to statistically assess the association between the position of nodes and the occurrence of outbreaks. By using social network analysis techniques combined with a classification method and a logistic model, we finally identified 3 nodes (set of villages), of the 387 in the initial network, to focus on for surveillance and control in the Lac Alaotra area. This result is of primary importance in the ongoing efforts to effectively improve the wellbeing of people in the region.

Analysis of Swine Movement in Four Canadian Regions: Network Structure and Implications for Disease Spread

Direct and indirect contacts among animal holdings are important in the spread of infectious diseases. The objectives of this study were to describe networks of pig movements and the sharing of trucks used for those movements between swine farms in four Canadian regions using network analysis tools and to obtain contact parameters for infectious disease spread simulation models. Four months of swine movement data from a pilot pig traceability programme were used. Two types of networks were created using three time scales (weekly, monthly and the full study period): one-mode networks of farm-to-farm direct contact representing animal shipments and two-mode networks representing the sharing of trucks between farms. Contact patterns among farms were described by estimating a range of relevant network measures. The overall network neglecting the four regions consisted of 145 farms, which were connected by 261 distinct links. A total of 184 trucks were used to transport 2043 shipments of pigs during the study period. The median in- and out-degree for the overall one-mode network was 1 and ranged from 0 to 26 and 0 to 10, respectively. The overall one-mode network had heterogeneous degree distribution, a high clustering coefficient and shorter average path length than would be expected for randomly generated networks of similar size. On average one truck was shared by four farms in the overall network, or by three farms when considered the monthly and weekly networks. Degree distribution of the two-mode overall network demonstrated characteristics of power-law distribution. For more than 50% of shipments on any given day, the same truck was used for at least one other shipment. Findings from this study are in agreement with previous work, which suggested that swine movement networks exhibit small-world and scale-free topologies. Furthermore, trucks used for the shipment of pigs can play an important role in connecting otherwise unconnected farms and may increase the spread of disease.

A survey of visitors on Swedish livestock farms with reference to the spread of animal diseases

Background

In addition to livestock movements, other between-farm contacts such as visitors may contribute to the spread of contagious animal diseases. Knowledge about such contacts is essential for contingency planning. Preventive measures, risk-based surveillance and contact tracing may be facilitated if the frequency and type of between-farm contacts can be assessed for different types of farms. The aim of this study was to investigate the frequency and types of visitors on farms with cloven-hoofed animals in Sweden and to analyse whether there were differences in the number of visitors attributable to region, season, and type of herd. Data were collected from Swedish farmers through contact-logs covering two-week periods during four different seasons.

Results

In total, 482 (32%) farmers filled in the contact log for at least one period and the data represent 18,416 days. The average number of professional and non-professional visitors per day was 0.3 and 0.8, respectively. Whereas the number of professional visitors seemed to increase with increasing herd size, this relation was not seen for non-professional visits. The mean numbers of visitors per day were highest in the summer and in the farm category ‘small mixed farm’. Reports of the visitors’ degree of contact with the animals showed that veterinarians, AI-technicians, animal transporters and neighbours were often in direct contact with the animals or entered the stables and 8.8% of the repairmen were also in direct contact with animals, which was unexpected. In a multivariable analysis, species, herd size and season were significantly associated with the number of professional visitors as well as the number of visitors in direct contact with the animals.

Conclusion

In conclusion there was a large variation between farms in the number and type of contacts. The number of visitors that may be more likely to spread diseases between farms was associated with animal species and herd size.

Relative associations of cattle movements, local spread, and biosecurity with bovine viral diarrhoea virus (BVDV) seropositivity in beef and dairy herds

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.

Cattle producers' perceptions of biosecurity

BACKGROUND

The limited use of biosecurity practices by many in the farming community is likely to be due to a range of factors; further understanding of this issue is required. In this study, attitudes and behaviours of producers relating to selected biosecurity practices and the farming industry were studied by interviewing cattle farmers within a 100 km2 study area in north-west England using an interview-based questionnaire.

RESULTS

Most producers appeared to be familiar with the broad concept of the term biosecurity, although risks due to indirect contacts, rather than direct (animal) contacts, were more frequently highlighted. Most producers felt the nominated biosecurity practices were in some way useful, however there was not always agreement between the usefulness of a practice and it being undertaken, and vice versa. In agreement with other studies conducted in the UK, farmers most preferred to obtain information and advice on biosecurity from private veterinarians, but also highlighted DEFRA as a source.

CONCLUSIONS

This study highlights the importance of understanding the motivators and barriers behind the uptake of biosecurity practices on farms, as perceptions are variable. Further understanding of these issues is needed in order to more effectively communicate information in regards to herd health and disease prevention. By identifying differences in producers' attitudes, programs can be tailored specifically to individuals' needs.

Distinguishing between indirect and direct modes of transmission using epidemiological time series

Pathogen transmission can involve direct and/or indirect pathways. Using theoretical models, in this study we ask, "do directly and indirectly transmitted pathogens yield different population-level epidemiological dynamics?" and "can the transmission pathway be inferred from population-level epidemiological data?" Our approach involves comparing the continuous-time dynamics of a class of compartmental epidemiological models with direct versus environmentally mediated indirect transmission pathways. Combing analytical theory and numerical simulations we show that models with direct and indirect transmission can produce quantitatively similar time series when the pathogen cannot reproduce in the environment, particularly when the environmental pathogen dynamics are fast. We apply these results to a previous study on chronic wasting disease and show that identifying the transmission pathway is more difficult than previously acknowledged. Our analysis and simulations also yield conditions under which numerical differences can potentially identify the transmission route in oscillating endemic systems and systems where the environmental pathogen dynamics are not fast. This work begins to identify how differences in the transmission pathway can result in quantitatively different epidemiological dynamics and how those differences can be used to identify the transmission pathway from population level time series.

Determinants of biosecurity behaviour of British cattle and sheep farmers-a behavioural economics analysis

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.

Bioexclusion of diseases from dairy and beef farms: risks of introducing infectious agents and risk reduction strategies

Infectious disease represents a major threat to the productivity and welfare of cattle herds throughout the world. The introduction of infectious agents into dairy and beef farms may be through direct transmission (purchased cattle, reintroduced resident cattle and contact with contiguous cattle) or indirect transmission (fomites, visitors, other species, and biological materials) and this article reviews the evidence supporting these transmission routes. In the absence of eradication programmes for many endemic infectious diseases, bioexclusion is the key management process for risk reduction. Various ameliorative bioexclusion strategies have been recommended and the evidence supporting these protocols is considered.

Optimizing surveillance for livestock disease spreading through animal movements

The spatial propagation of many livestock infectious diseases critically depends on the animal movements among premises; so the knowledge of movement data may help us to detect, manage and control an outbreak. The identification of robust spreading features of the system is however hampered by the temporal dimension characterizing population interactions through movements. Traditional centrality measures do not provide relevant information as results strongly fluctuate in time and outbreak properties heavily depend on geotemporal initial conditions. By focusing on the case study of cattle displacements in Italy, we aim at characterizing livestock epidemics in terms of robust features useful for planning and control, to deal with temporal fluctuations, sensitivity to initial conditions and missing information during an outbreak. Through spatial disease simulations, we detect spreading paths that are stable across different initial conditions, allowing the clustering of the seeds and reducing the epidemic variability. Paths also allow us to identify premises, called sentinels, having a large probability of being infected and providing critical information on the outbreak origin, as encoded in the clusters. This novel procedure provides a general framework that can be applied to specific diseases, for aiding risk assessment analysis and informing the design of optimal surveillance systems.

Biosecurity on cattle farms: a study in north-west England

BACKGROUND

Few studies have considered in detail the range of biosecurity practices undertaken on cattle farms, particularly within the UK. In this study, 56 cattle farmers in a 100 km² area of north-west England were questioned regarding their on-farm biosecurity practices, including those relating to animal movements, equipment sharing and companies and contractors visiting the farms.

METHODOLOGY/PRINCIPAL FINDINGS

There was great variation between farms in terms of the type of, and extent to which, biosecurity was carried out. For example, the majority of farmers did not isolate stock bought onto the farm, but a small proportion always isolated stock. Many farmers administered treatments post-movement, primarily vaccinations and anthelmintics, but very few farms reported carrying out any health checks after moving animals on. In addition, there appeared to be much variation in the amount of biosecurity carried out by the different companies and contractors visiting the farms. Deadstock collectors and contracted animal waste spreaders, although likely to have a high potential for contact with infectious agents, were reported to infrequently disinfect themselves and their vehicles.

CONCLUSIONS/SIGNIFICANCE

These findings suggest that although certain biosecurity practices are undertaken, many are carried out infrequently or not at all. This may be due to many factors, including cost (in time and money), lack of proven efficacies of practices and lack of relevant education of veterinary surgeons, producers and other herd health specialists. Further research exploring the reasons for the lack of uptake is imperative if preventive medicine is to be utilised fully by the farming industry.

Potential for epidemic take-off from the primary outbreak farm via livestock movements

BACKGROUND

We consider the potential for infection to spread in a farm population from the primary outbreak farm via livestock movements prior to disease detection. We analyse how this depends on the time of the year infection occurs, the species transmitting, the length of infectious period on the primary outbreak farm, location of the primary outbreak, and whether a livestock market becomes involved. We consider short infectious periods of 1 week, 2 weeks and 4 weeks, characteristic of acute contagious livestock diseases. The analysis is based on farms in Scotland from 1 January 2003 to 31 July 2007.

RESULTS

The proportion of primary outbreaks from which an acute contagious disease would spread via movement of livestock is generally low, but exhibits distinct annual cyclicity with peaks in May and August. The distance that livestock are moved varies similarly: at the time of the year when the potential for spread via movements is highest, the geographical spread via movements is largest. The seasonal patterns for cattle differ from those for sheep whilst there is no obvious seasonality for pigs. When spread via movements does occur, there is a high risk of infection reaching a livestock market; infection of markets can amplify disease spread. The proportion of primary outbreaks that would spread infection via livestock movements varies significantly between geographical regions.

CONCLUSIONS

In this paper we introduce a set-up for analysis of movement data that allows for a generalized assessment of the risk associated with infection spreading from a primary outbreak farm via livestock movements, applying this to Scotland, we assess how this risk depends upon the time of the year, species transmitting, location of the farm and other factors.

Network of contacts between cattle herds in a French area affected by bovine tuberculosis in 2010

France attained 'Officially Tuberculosis-Free' status in 2000. However, the Côte d'Or department (a French administrative unit) has since seen an increase in bovine tuberculosis (bTB) cases, with 35% of cases attributed to neighbourhood contamination. The aim of this study was to investigate the characteristics of neighbourhood contacts in an area affected by bTB in 2010, through the use of social network methods. We carried out a survey to determine the frequency and distribution of between-herd contacts in an area containing 22 farms. Contacts were weighted, as not all types of contact carried the same risk of bTB transmission. Cattle movement was considered to be associated with the highest risk, but was not observed within the studied area during the study period. Contact with wild boars was the most frequent type of contact, but was associated with a very low risk. Direct cattle-to-cattle contacts in pasture and contacts with badger latrines were less frequent, but entailed a greater risk of M. bovis transmission. Centrality values were heterogeneous in these two networks. This would enable the disease to spread more rapidly at the start of epidemics than in a perfect randomly mixed population. However, this situation should also result in the total number of infected herds being smaller. We attributed 95% of the contacts to direct contact in pasture or contact with wild boars or badger latrines. Other kinds of contact occurred less frequently (equipment sharing, cattle straying) or did not occur at all (attendance at a show). Most of the contact types were correlated, but none was sufficient in itself to account for all contacts between one particular farm and its neighbours. Contacts with neighbours therefore represent a challenge for the implementation or improvement of control measures.

Dynamical patterns of cattle trade movements

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases. Results show how the stationarity of statistical distributions coexists with a strong and non-trivial evolutionary dynamics at the node and link levels, on all timescales. Traditional static views of the displacement network hide important patterns of structural changes affecting nodes' centrality and farms' spreading potential, thus limiting the efficiency of interventions based on partial longitudinal information. By fully taking into account the longitudinal dimension, we propose a novel definition of dynamical motifs that is able to uncover the presence of a temporal arrow describing the evolution of the system and the causality patterns of its displacements, shedding light on mechanisms that may play a crucial role in the definition of preventive actions.

A novel field-based approach to validate the use of network models for disease spread between dairy herds

The introduction of a centralized system for recording cattle movements in the UK has provided a framework for network-based models for disease spread. However, there are many types of non-reportable contacts between farms which may play a role in disease spread. The lack of real pathogen data with which to test network models makes it difficult to assess whether reported data adequately captures the risk-potential network between farms and improves the accuracy of disease forecasts. A novel multi-disciplinary approach is described whereby network-based models, built upon reported cattle movements and non-reportable local contacts between study farms, are parameterized using field data on bovine Staphylococcus aureus strains. Reported cattle movements were found to play a role in strain spread between farms, but other contacts via farm visitors were also correlated with strain distribution, suggesting that parameterizing contact networks using cattle-tracing data alone may not adequately capture the disease dynamics.

Bayesian analysis of animal movements related to factors at herd and between herd levels: Implications for disease spread modeling

A method to assess the influence of between herd distances, production types and herd sizes on patterns of between herd contacts is presented. It was applied on pig movement data from a central database of the Swedish Board of Agriculture. To determine the influence of these factors on the contact between holdings we used a Bayesian model and Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution of model parameters. The analysis showed that the contact pattern via animal movements is highly heterogeneous and influenced by all three factors, production type, herd size, and distance between holdings. Most production types showed a positive relationship between maximum capacity and the probability of both incoming and outgoing movements. In agreement with previous studies, holdings also differed in both the number of contacts as well as with what holding types contact occurred with. Also, the scale and shape of distance dependence in contact probability was shown to differ depending on the production types of holdings.To demonstrate how the methodology may be used for risk assessment, disease transmissions via animal movements were simulated with the model used for analysis of contacts, and parameterized by the analyzed posterior distribution. A Generalized Linear Model showed that herds with production types Sow pool center, Multiplying herd and Nucleus herd have higher risk of generating a large number of new infections. Multiplying herds are also expected to generate many long distance transmissions, while transmissions generated by Sow pool centers are confined to more local areas. We argue that the methodology presented may be a useful tool for improvement of risk assessment based on data found in central databases.

Epidemics and control strategies for diseases of farmed salmonids: a parameter study

The susceptibility of the English and Welsh fish farming and fisheries industry to emergent diseases is assessed using a stochastic simulation model. The model dynamics operate on a network comprising directed transport and river contacts, as well as undirected local and fomite transmissions. The directed connections cause outward transmission risk to be geographically more confined than inward risk. We consider reactive, proactive, and hybrid methods of control which correspond to a mixture of policy and the ease of disease detection. An explicit investigation of the impact of laboratory capacity is made. General quantified guidelines are derived to mitigate future epidemics.

Stochastic model of the potential spread of highly pathogenic avian influenza from an infected commercial broiler operation in Georgia

The potential spread of highly pathogenic avian influenza among commercial broiler farms in Georgia, U. S. A., was mathematically modeled. The dynamics of the spread within the first infected flock were estimated using an SEIR (susceptible-exposed-infectious-recovered) deterministic model, and predicted that grower detection of flock infection is most likely 5 days after virus introduction. Off-farm spread of virus was estimated stochastically for this period, predicting a mean range of exposed farms from 0-5, depending on the density of farms in the area. Modeled off-farm spread was most frequently associated with feed trucks (highest daily probability and number of farm visits) and with company personnel or hired help (highest level of bird contact).