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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., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In the French bovine tuberculosis (bTB) surveillance program, tracing-on and back investigations have a major importance as, in 2016, they represented about 21 % of the detected outbreaks. Building on our previous work on the other surveillance system components (Poirier et al., 2019), we evaluated for the first time the sensitivity and the cost of the two existing protocols of bTB's tracing-on investigations trough scenario tree modelling with a stochastic approach. We used French databases (national database for bovine identification and database recording all bTB surveillance and control results) and direct and indirect costs collected in a previous study. These assessments allowed us to calculate the cost-effectiveness index (cost/sensitivity) of each tracing-on protocol. In the first protocol (trace-and-cull protocol), the animal(s) linking the farm to an outbreak are systematically culled for bacteriology, PCR and histology testing. In the second protocol (trace-and-test protocol), the traced animal is culled only if it had non-negative result to an intradermal cervical comparative tuberculin test (ICCT). We estimated herd sensitivity of the two tracing-on protocols for 12 herd types defined by their production type, size and herd turnover. For the trace-and-cull protocol, mean herd sensitivity was estimated between 67.3 % [66.8-67.7] CI95 % and 89.2 % [88.7-89.7] CI95 % and between 51.2 % [50.8-51.5] CI95 % and 73.1 % [72.6-73.6] CI95 % for the trace-and-test protocol, depending on herd type. The trace-and-cull protocol was between 278 €/herd and 717 €/herd more expensive than the trace-and-test protocol, depending on herd type. Regardless of herd type, the trace-and-cull protocol had the smaller cost/sensitivity ratio and was therefore the most cost-effective protocol. That work showed that systematically culling traced animals to perform bacteriology and PCR on them (trace-and-cull protocol) is associated with a better herd sensitivity and is more cost-effective for all herd types. That is consistent with French veterinary authorities' recommendations but does not account for sociological aspects such as the bond between the farmer and his animals. Yet, cost-effectiveness difference was minor in small dairy and beef herds with a low turnover, suggesting the protocol could be chosen depending on the epidemiological context in those herds., Competing Interests: Declaration of Competing Interest None., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Canine influenza virus (CIV) A(H3N2) was identified in 104 dogs in Ontario, Canada, during December 28, 2017-October 30, 2018, in distinct epidemiologic clusters. High morbidity rates occurred within groups of dogs, and kennels and a veterinary clinic were identified as foci of infection. Death attributable to CIV infection occurred in 2 (2%) of 104 diagnosed cases. A combination of testing of suspected cases, contact tracing and testing, and 28-day isolation of infected dogs was used, and CIV transmission was contained in each outbreak. Dogs recently imported from Asia were implicated as the source of infection. CIV H3N2 spread rapidly within groups in this immunologically naive population; however, containment measures were apparently effective, demonstrating the potential value of prompt diagnosis and implementation of CIV control measures.

Disease transmission models often assume homogenous mixing. This assumption, however, has the potential to misrepresent the disease dynamics for populations in which contact patterns are non-random. A disease transmission model with an SEIR structure was used to compare the effect of weighted and unweighted empirical equine contact networks to weighted and unweighted theoretical networks generated using random mixing. Equine influenza was used as a case study. Incidence curves generated with the unweighted empirical networks were similar in epidemic duration (5-8 days) and peak incidence (30.8-46.4%). In contrast, the weighted empirical networks resulted in a more pronounced difference between the networks in terms of the epidemic duration (8-15 days) and the peak incidence (5-25%). The incidence curves for the empirical networks were bimodal, while the incidence curves for the theoretical networks were unimodal. The incorporation of vaccination and isolation in the model caused a decrease in the cumulative incidence for each network, however, this effect was only seen at high levels of vaccination and isolation for the complete network. This study highlights the importance of using empirical networks to describe contact patterns within populations that are unlikely to exhibit random mixing such as equine populations.

Between October 2016 and December 2017, several European Countries had been involved in a massive Highly Pathogenic Avian Influenza (HPAI) epidemic sustained by H5N8 subtype virus. Starting on December 2016, also Italy was affected by H5N8 HPAI virus, with cases occurring in two epidemic waves: the first between December 2016 and May 2017, and the second in July-December 2017. Eighty-three outbreaks were recorded in poultry, 67 of which (80.72%) occurring in the second wave. A total of 14 cases were reported in wild birds. Epidemiological information and genetic analyses were conjointly used to get insight on the spread dynamics. Analyses indicated multiple introductions from wild birds to the poultry sector in the first epidemic wave, and noteworthy lateral spread from October 2017 in a limited geographical area with high poultry densities. Turkeys, layers and backyards were the mainly affected types of poultry production. Two genetic sub-groups were detected in the second wave in non-overlapping geographical areas, leading to speculate on the involvement of different wild bird populations. The integration of epidemiological data and genetic analyses allowed to unravel the transmission dynamics of H5N8 virus in Italy, and could be exploited to timely support in implementing tailored control measures.

Understanding host interactions that lead to pathogen transmission is fundamental to the prediction and control of epidemics 1-5 . Although the majority of transmissions often occurs within social groups 6-9 , the contribution of connections that bridge groups and species to pathogen dynamics is poorly understood 10-12 . These cryptic connections-which are often indirect or infrequent-provide transmission routes between otherwise disconnected individuals and may have a key role in large-scale outbreaks that span multiple populations or species. Here we quantify the importance of cryptic connections in disease dynamics by simultaneously characterizing social networks and tracing transmission dynamics of surrogate-pathogen epidemics through eight communities of bats. We then compared these data to the invasion of the fungal pathogen that causes white-nose syndrome, a recently emerged disease that is devastating North American bat populations 13-15 . We found that cryptic connections increased links between individuals and between species by an order of magnitude. Individuals were connected, on average, to less than two per cent of the population through direct contact and to only six per cent through shared groups. However, tracing surrogate-pathogen dynamics showed that each individual was connected to nearly fifteen per cent of the population, and revealed widespread transmission between solitarily roosting individuals as well as extensive contacts among species. Connections estimated from surrogate-pathogen epidemics, which include cryptic connections, explained three times as much variation in the transmission of the fungus that causes white-nose syndrome as did connections based on shared groups. These findings show how cryptic connections facilitate the community-wide spread of pathogens and can lead to explosive epidemics.

The analysis of the pork value chain is becoming key to understanding the risk of infectious disease dissemination in the swine industry. In this study, we used social network analysis to characterize the swine shipment network structure and properties in a typical multisite swine production system in the US. We also aimed to evaluate the association between network properties and porcine respiratory and reproductive syndrome virus (PRRSV) transmission between production sites. We analyzed the 109,868 swine shipments transporting over 93 million swine between more than 500 production sites from 2012 to 2014. A total of 248 PRRSV positive occurrences were reported from 79 production sites during those 3 years. The temporal dynamics of swine shipments was evaluated by computing network properties in one-month and three-month networks. The association of PRRS occurrence in sow farms with centrality properties from one-month and three-month networks was assessed by using the multilevel logistic regression. All monthly networks showed a scale-free network topology with positive degree assortativity. The regression model revealed that out-degree centrality had a negative association with PRRS occurrence in sow farms in both one-month and three-month networks [OR=0.79 (95% CI, 0.63-0.99) in one-month network and 0.56 (95% CI, 0.36, 0.88) in three-month network] and in-closeness centrality model was positively associated with PRRS occurrence in sow farms in the three-month network [OR=2.45 (95% CI, 1.14-5.26)]. We also describe how the occurrence of porcine epidemic diarrheac (PED) outbreaks severely affected the network structure as well as the PRRS occurrence reports and its association with centrality measures in sow farms. The structure of the swine shipment network and the connectivity between production sites influenced on the PRRSV transmission. The use of network topology and characteristics combining with spatial analysis based on fine scale geographical location of production sites will be useful to inform the design of more cost-efficient, risk-based surveillance and control measures for PRRSV as well as other diseases in the US swine industry., (Copyright © 2017 Elsevier B.V. All rights reserved.)

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., Competing Interests: The authors have declared that no competing interests exist.

Effective management of infectious disease relies upon understanding mechanisms of pathogen transmission. In particular, while models of disease dynamics usually assume transmission through direct contact, transmission through environmental contamination can cause different dynamics. We used Global Positioning System (GPS) collars and proximity-sensing contact-collars to explore opportunities for transmission of Mycobacterium bovis [causal agent of bovine tuberculosis] between cattle and badgers (Meles meles). Cattle pasture was badgers' most preferred habitat. Nevertheless, although collared cattle spent 2914 collar-nights in the home ranges of contact-collared badgers, and 5380 collar-nights in the home ranges of GPS-collared badgers, we detected no direct contacts between the two species. Simultaneous GPS-tracking revealed that badgers preferred land > 50 m from cattle. Very infrequent direct contact indicates that badger-to-cattle and cattle-to-badger M. bovis transmission may typically occur through contamination of the two species' shared environment. This information should help to inform tuberculosis control by guiding both modelling and farm management., (© 2016 John Wiley & Sons Ltd/CNRS.)

Pestiviruses infect a wide variety of animals of the order Artiodactyla, with bovine viral diarrhea virus (BVDV) being an economically important pathogen of livestock globally. BVDV is maintained in the cattle population by infecting fetuses early in gestation and, thus, by generating persistently infected (PI) animals that efficiently transmit the virus throughout their lifetime. In 2008, Switzerland started a national control campaign with the aim to eradicate BVDV from all bovines in the country by searching for and eliminating every PI cattle. Different from previous eradication programs, all animals of the entire population were tested for virus within one year, followed by testing each newborn calf in the subsequent four years. Overall, 3,855,814 animals were tested from 2008 through 2011, 20,553 of which returned an initial BVDV-positive result. We were able to obtain samples from at least 36% of all initially positive tested animals. We sequenced the 5' untranslated region (UTR) of more than 7400 pestiviral strains and compiled the sequence data in a database together with an array of information on the PI animals, among others, the location of the farm in which they were born, their dams, and the locations where the animals had lived. To our knowledge, this is the largest database combining viral sequences with animal data of an endemic viral disease. Using unique identification tags, the different datasets within the database were connected to run diverse molecular epidemiological analyses. The large sets of animal and sequence data made it possible to run analyses in both directions, i.e., starting from a likely epidemiological link, or starting from related sequences. We present the results of three epidemiological investigations in detail and a compilation of 122 individual investigations that show the usefulness of such a database in a country-wide BVD eradication program., (Copyright © 2015 Elsevier B.V. All rights reserved.)

An outbreak of the highly contagious animal disease classical swine fever (CSF) requires the selection of an optimal control strategy. The choice of a control strategy is a decision process depending on different aspects. Besides epidemiology, economic and ethical/social aspects must be taken into account. In this study, multicriteria decision-making (MCDM) was used to evaluate six control strategies for two regions with different farm densities. A strategy including only the minimum EU control measures and the traditional control strategy based on preventive culling were compared to alternative control strategies using emergency vaccination and/or rapid PCR testing ('emergency vaccination', 'test to slaughter', 'test to control' and 'vaccination in conjunction with rapid testing'). The MACBETH approach was used in order to assess the three main criteria (epidemiology, economics and ethical/social aspects). Subcriteria with both quantitative and qualitative performance levels were translated into a normalized scale. The Choquet integral approach was adopted to obtain a ranking of the six CSF control strategies based on the three main criteria, taking interactions into account. Three different rankings of the importance of the main criteria, which were to reflect the potential perceptions of stakeholders, were examined. Both the region under investigation and the ranking of the main criteria had an influence on the 'best' choice. Alternative control strategies were favourable to the minimum EU control and the traditional control measures independent of the farm density. Because the choice of the 'best' control strategy does not solely depend on the epidemiological efficiency, MCDM can help to find the best solution. Both MACBETH and the Choquet integral approach are feasible MCDM approaches. MACBETH only needs a qualitative evaluation and is therefore a comparatively intuitive approach. The Choquet integral does not only take the importance of the criteria into account but also the interaction between them., (© 2014 Blackwell Verlag GmbH.)

Elevated risk of disease transmission is considered a major cost of sociality, although empirical evidence supporting this idea remains scant. Variation in spatial cohesion and the occurrence of social interactions may have profound implications for patterns of interindividual parasite transmission. We used a social network approach to shed light on the importance of different aspects of group-living (i.e. within-group associations versus physical contact) on patterns of parasitism in a neotropical primate, the brown spider monkey (Ateles hybridus), which exhibits a high degree of fission-fusion subgrouping. We used daily subgroup composition records to create a 'proximity' network, and built a separate 'contact' network using social interactions involving physical contact. In the proximity network, connectivity between individuals was homogeneous, whereas the contact network highlighted high between-individual variation in the extent to which animals had physical contact with others, which correlated with an individual's age and sex. The gastrointestinal parasite species richness of highly connected individuals was greater than that of less connected individuals in the contact network, but not in the proximity network. Our findings suggest that among brown spider monkeys, physical contact impacts the spread of several common parasites and supports the idea that pathogen transmission is one cost associated with social contact., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

A major risk factor in the spread of diseases between holdings is the transport of live animals. This study analysed the animal movements of the pork supply chain of a producer group in Northern Germany. The parameters in-degree and out-degree, ingoing and outgoing infection chain, betweenness and ingoing and outgoing closeness were measured using dynamic network analysis to identify holdings with central positions in the network and to characterize the overall network topology. The potential maximum epidemic size was also estimated. All parameters were calculated for three time periods: the 3-yearly network, the yearly and the monthly networks. The yearly and the monthly networks were more fragmented than the 3-yearly network. On average, one-third of the holdings were isolated in the yearly networks and almost three quarters in the monthly networks. This represented an immense reduction in the number of holdings participating in the trade of the monthly networks. The overall network topology showed right-skewed distributions for all calculated centrality parameters indicating that network resilience was high concerning the random removal of holdings. However, for a targeted removal of holdings according to their centrality, a rapid fragmentation of the trade network could be expected. Furthermore, to capture the real importance of holdings for disease transmission, indirect trade contacts (infection chain) should be considered. In contrast to the parameters regarding direct trade contacts (degree), the infection chain parameter did not underestimate the potential risk of disease transmission. This became more obvious, the longer the observed time period was. For all three time periods, the results for the estimation of the potential maximum epidemic size illustrated that the outgoing infection chain should be chosen. It considers the chronological order and the directed nature of the contacts and has no restrictions such as the strongly connected components of a cyclic network., (© 2013 Blackwell Verlag GmbH.)

The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals ("agents") within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets., (Copyright © 2014 Elsevier B.V. All rights reserved.)

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., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Summary: In case of a classical swine fever outbreak in the European Union (EU), its control is based upon the culling of swine on infected farms, movement restrictions in the protection and surveillance zones, and contact tracing. Additionally, preventive culling may be carried out. Emergency vaccination and rapid PCR testing are discussed as alternatives to avoid this measure. An outbreak of classical swine fever and the success of its control are influenced by different factors. Using a spatial and temporal Monte-Carlo simulation model the control strategies 'Restriction Zone', 'Traditional Control', 'Emergency Vaccination', 'Test To Slaughter', 'Test To Control' and 'Vaccination in conjunction with Rapid Testing' were compared under various conditions. Farm density, compliance with movement restrictions and delay in the establishment of an emergency vaccination were analysed as influencing factors. It was found that all these factors had a significant influence on the number of infected and culled farms. In a low-density region, the basic measures are sufficient to control an epidemic, provided strict compliance with movement restrictions is adhered to. In a high-density region, additional measures are necessary. They can compensate non-strict compliance with movement restriction to a certain extent. In the high-density region, 'Emergency Vaccination' and 'Vaccination in conjunction with Rapid Testing' reached the same level of infected farms as 'Traditional Control', independent of the value of compliance with movement restrictions. However, in the case of an emergency vaccination, an early start to the vaccination campaign is essential for successful disease control., (© 2012 Blackwell Verlag GmbH.)

Background: During outbreak of livestock diseases, contact tracing can be an important part of disease control. Animal movements can also be of relevance for risk-based surveillance and sampling, i.e. both when assessing consequences of introduction or likelihood of introduction. In many countries, animal movement data are collected with one of the major objectives to enable contact tracing. However, often an analytical step is needed to retrieve appropriate information for contact tracing or surveillance., Results: In this study, an open source tool was developed to structure livestock movement data to facilitate contact-tracing in real time during disease outbreaks and for input in risk-based surveillance and sampling. The tool, EpiContactTrace, was written in the R-language and uses the network parameters in-degree, out-degree, ingoing contact chain and outgoing contact chain (also called infection chain), which are relevant for forward and backward tracing respectively. The time-frames for backward and forward tracing can be specified independently and search can be done on one farm at a time or for all farms within the dataset. Different outputs are available; datasets with network measures, contacts visualised in a map and automatically generated reports for each farm either in HTML or PDF-format intended for the end-users, i.e. the veterinary authorities, regional disease control officers and field-veterinarians. EpiContactTrace is available as an R-package at the R-project website (http://cran.r-project.org/web/packages/EpiContactTrace/)., Conclusions: We believe this tool can help in disease control since it rapidly can structure essential contact information from large datasets. The reproducible reports make this tool robust and independent of manual compilation of data. The open source makes it accessible and easily adaptable for different needs.

Background: When modelling infectious diseases, accurately capturing the pattern of dissemination through space is key to providing optimal recommendations for control. Mathematical models of disease spread in livestock, such as for foot-and-mouth disease (FMD), have done this by incorporating a transmission kernel which describes the decay in transmission rate with increasing Euclidean distance from an infected premises (IP). However, this assumes a homogenous landscape, and is based on the distance between point locations of farms. Indeed, underlying the spatial pattern of spread are the contact networks involved in transmission. Accordingly, area-weighted tessellation around farm point locations has been used to approximate field-contiguity and simulate the effect of contiguous premises (CP) culling for FMD. Here, geographic data were used to determine contiguity based on distance between premises' fields and presence of landscape features for two sample areas in Scotland. Sensitivity, positive predictive value, and the True Skill Statistic (TSS) were calculated to determine how point distance measures and area-weighted tessellation compared to the 'gold standard' of the map-based measures in identifying CPs. In addition, the mean degree and density of the different contact networks were calculated., Results: Utilising point distances <1 km and <5 km as a measure for contiguity resulted in poor discrimination between map-based CPs/non-CPs (TSS 0.279-0.344 and 0.385-0.400, respectively). Point distance <1 km missed a high proportion of map-based CPs; <5 km point distance picked up a high proportion of map-based non-CPs as CPs. Area-weighted tessellation performed best, with reasonable discrimination between map-based CPs/non-CPs (TSS 0.617-0.737) and comparable mean degree and density. Landscape features altered network properties considerably when taken into account., Conclusion: The farming landscape is not homogeneous. Basing contiguity on geographic locations of field boundaries and including landscape features known to affect transmission into FMD models are likely to improve individual farm-level accuracy of spatial predictions in the event of future outbreaks. If a substantial proportion of FMD transmission events are by contiguous spread, and CPs should be assigned an elevated relative transmission rate, the shape of the kernel could be significantly altered since ability to discriminate between map-based CPs and non-CPs is different over different Euclidean distances.

Tuberculosis (TB) due to infection with Mycobacterium bovis is transmitted between cattle and badgers (Meles meles) in the UK and Ireland but it is unclear where or when transmission occurs. We investigated direct and indirect interactions between badgers and cattle using automated proximity loggers on animals and at badger latrines located on pasture, in an area of south-west England with a high-density badger population. Direct contacts (interactions within 1.4 m) between badgers and cattle at pasture were very rare (four out of >500000 recorded animal-to-animal contacts) despite ample opportunity for interactions to occur. Indirect interactions (visits to badger latrines by badgers and cattle) were two orders of magnitude more frequent than direct contacts: 400 visits by badgers and 1700 visits by cattle were recorded. This suggests that indirect contacts might be more important than direct contacts in terms of disease transmission at pasture. The TB infection status of individual badgers (ascribed with 93% accuracy using three diagnostic tests) did not affect the frequency or duration of their visits to latrines located on pasture grazed by cattle. Nevertheless, there was wide variation in contact behaviour between individuals, which highlights the importance of understanding heterogeneity in contact patterns when developing strategies to control disease spread in wildlife and livestock.

Classical swine fever (CSF) outbreaks can cause enormous losses in naïve pig populations. How to best minimize the economic damage and number of culled animals caused by CSF is therefore an important research area. The baseline CSF control strategy in the European Union and Switzerland consists of culling all animals in infected herds, movement restrictions for animals, material and people within a given distance to the infected herd and epidemiological tracing of transmission contacts. Additional disease control measures such as pre-emptive culling or vaccination have been recommended based on the results from several simulation models; however, these models were parameterized for areas with high animal densities. The objective of this study was to explore whether pre-emptive culling and emergency vaccination should also be recommended in low- to moderate-density areas such as Switzerland. Additionally, we studied the influence of initial outbreak conditions on outbreak severity to improve the efficiency of disease prevention and surveillance. A spatial, stochastic, individual-animal-based simulation model using all registered Swiss pig premises in 2009 (n=9770) was implemented to quantify these relationships. The model simulates within-herd and between-herd transmission (direct and indirect contacts and local area spread). By varying the four parameters (a) control measures, (b) index herd type (breeding, fattening, weaning or mixed herd), (c) detection delay for secondary cases during an outbreak and (d) contact tracing probability, 112 distinct scenarios were simulated. To assess the impact of scenarios on outbreak severity, daily transmission rates were compared between scenarios. Compared with the baseline strategy (stamping out and movement restrictions) vaccination and pre-emptive culling neither reduced outbreak size nor duration. Outbreaks starting in a herd with weaning piglets or fattening pigs caused higher losses regarding to the number of culled premises and were longer lasting than those starting in the two other index herd types. Similarly, larger transmission rates were estimated for these index herd type outbreaks. A longer detection delay resulted in more culled premises and longer duration and better transmission tracing increased the number of short outbreaks. Based on the simulation results, baseline control strategies seem sufficient to control CSF in low-medium animal-dense areas. Early detection of outbreaks is crucial and risk-based surveillance should be focused on weaning piglet and fattening pig premises., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: More and more countries hold databases on cattle movements. The primary purpose of the registration of cattle movements is to provide data for quick tracing of contagious animals in case of disease outbreaks and food safety scares. Nevertheless, these data can also be used for analytical studies to get insight into the nature of the contact structure between and within cattle holding types. This paper focuses on the effect post-2001 FMD movement regulations have had on the number of cattle movements between different and within the same cattle holding types. Important characteristics and dynamics of cattle movement patterns of Dutch cattle holding types were identified using data on cattle movements after the 2001 FMD outbreak., Results: The results showed that in 2001, just after the FMD outbreak when strict movement restriction regulations were in force, a reduced number of cattle movements was seen compared to before the FMD outbreak. However, the number of cattle movements off-farm for live trade and the number of imported cattle increased in the period 2002-2004 to higher levels than expected, i.e. to levels almost as high as before the FMD outbreak, despite operative movement restriction regulations. As the number of cattle movements to and from traders strongly decreased just after the FMD outbreak in 2001, traders regained their central role again in the network in the years 2002-2004., Conclusions: Quantifying the Dutch cattle contact structure between and within holding types up to 3.5 years after the FMD outbreak gave evidence that the post-FMD movement restriction regulations were not able to reduce the number of cattle movements in the longer term. With that the risk of a large epidemic increased. Quantifying contact structures based on animal movement data between different and within the same cattle holding types is important for targeting disease control and for assessing compliance with legislation.

Equine influenza is a highly contagious and widespread viral respiratory disease of horses and other equid species, characterised by fever and a harsh dry cough. In 2007, in the first reported outbreak in Australia, the virus spread through the horse populations of two states within 4 months. Most of the geographic spread occurred within the first 10 days and was associated with the movement of infected horses prior to the implementation of movement controls. This study applies social network analysis to describe spread of equine influenza between horse premises infected in the early outbreak period, identifying spread occurring through a contact network and secondary local spatial spread. Social networks were constructed by combining contact-tracing data on horse movements with a distance matrix between all premises holding horses infected within the first 10 days of the outbreak. These networks were analysed to provide a description of the epidemic, identify premises that were central to disease spread and to estimate the relative proportion of premises infected through infected horse movements and through local spatial spread. We then explored the effect of distance on disease spread by estimating the range of local spread (through direct contact, transmission on fomites and windborne transmission) based on the level of fragmentation in the network and also by directly estimating the shape of the outbreak's spatial transmission kernel. During the first 10 days of this epidemic, 197 horse premises were infected; 70 of these were included in the contact-traced network. Most local spread occurred within 5 km. Local spread was estimated to have occurred up to a distance of 15.3 km - based on the contact-and-proximity network - and at a very low incidence beyond this distance based on the transmission kernel estimate. Of the 70 premises in the contact network, spread to 14 premises (95% CI: 9, 20 premises) was likely to have occurred through local spatial spread from nearby infected premises, suggesting that 28.3% of spread in the early epidemic period was 'network-associated' (95% CI: 25.6, 31.0%). By constructing a 'maximal network' of contact and proximity (based on a distance cut-off of 15.3 km), 44 spatial clusters were described, and the horse movements that initiated infection in these locations were identified. Characteristics of the combined network, incorporating both spatial and underlying contact relationships between infected premises, explained the high rate of spread, the sequence of cluster formation and the widespread dispersal experienced in the early phase of this epidemic. These results can inform outbreak control planning by guiding the imposition of appropriate control zone diameters around infected premises and the targeting of surveillance and interventions., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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., (Copyright © 2012 Elsevier B.V. All rights reserved.)

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., (© 2011 Blackwell Verlag GmbH.)

Infection with Brucella canis has been diagnosed in Sweden for the first time. It was diagnosed in a three-year-old breeding bitch with reproductive disturbances. Fifteen in-contact dogs were tested repeatedly and all of them were negative for B. canis. The source of infection could not be defined. The present article describes the case and the measures undertaken and gives a short review over B. canis. Recommendations on how to avoid the infection in non-endemic countries are given.

Tracing movements could assist the implementation of bio-containment measures during a disease outbreak. To evaluate the potential for implementing a tracing system for a poultry supply chain in northern Vietnam, a four-month longitudinal study was conducted to identify marketing practices associated with poultry traceability. Poultry sold in batches were traced between farms and markets, and their traceability was assessed upon market arrival. A total of 315 batches were released from the farms; 37% arrived at a market, from which 57.3% were 'traceable'. The results of the multivariable analysis showed that traceability was associated with farms operating through no more than two traders (Odds ratio [OR] = 5.97, 95% CI 1.15-30.92) and batches brought to the market on the day of purchase (OR = 4.05, 95% CI 1.23-13.27). No specific incentives were provided to farmers or traders. Results suggest that there is potential for implementing a poultry traceability scheme, although the tracing methodology should be refined.

Over the past two decades, the poultry sector in China went through a phase of tremendous growth as well as rapid intensification and concentration. Highly pathogenic avian influenza virus (HPAIV) subtype H5N1 was first detected in 1996 in Guangdong province, South China and started spreading throughout Asia in early 2004. Since then, control of the disease in China has relied heavily on wide-scale preventive vaccination combined with movement control, quarantine and stamping out. This strategy has been successful in drastically reducing the number of outbreaks during the past 5years. However, HPAIV H5N1 is still circulating and is regularly isolated in traditional live bird markets (LBMs) where viral infection can persist, which represent a public health hazard for people visiting them. The use of social network analysis in combination with epidemiological surveillance in South China has identified areas where the success of current strategies for HPAI control in the poultry production sector may benefit from better knowledge of poultry trading patterns and the LBM network configuration as well as their capacity for maintaining HPAIV H5N1 infection. We produced a set of LBM network maps and estimated the associated risk of HPAIV H5N1 within LBMs and along poultry market chains, providing new insights into how live poultry trade and infection are intertwined. More specifically, our study provides evidence that several biosecurity factors such as daily cage cleaning, daily cage disinfection or manure processing contribute to a reduction in HPAIV H5N1 presence in LBMs. Of significant importance is that the results of our study also show the association between social network indicators and the presence of HPAIV H5N1 in specific network configurations such as the one represented by the counties of origin of the birds traded in LBMs. This new information could be used to develop more targeted and effective control interventions., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Human movements associated with poultry farming create contact networks that might facilitate transmission of avian influenza (AI) between farms during outbreaks. In Canada, no information is available about how these networks connect poultry farms. The purpose of this study was to document human contacts between commercial poultry farms in Ontario, Canada, to learn how AI might be transmitted during outbreaks. We used face-to-face interviews with people entering the farm biosecurity perimeter on four layer, one turkey and three broiler breeder poultry farms in Ontario to collect information on between-farm contacts and biosecurity practices. Over a four-day study period on each farm, a median of 10.5 people entered the farm biosecurity perimeter (range 2-31). Ninety-six per cent (111/118) of people consented to be interviewed. Of these, fifty-three per cent (59/111) had contact with one or more (median 2, degree range 1-14) other poultry farms within 72 h. A median of 25 (range 7-65) human contacts linked study farms to other poultry farms. The mean distance of between-farm contacts was 53 km. Eighty-six per cent of people who answered the biosecurity questions (94/109) reported using one or more biosecurity practices. However, on 7/8 farms, at least one person reported that they did not use any biosecurity practices. Fifty per cent of social visitors used biosecurity, whereas 96% of all other people used biosecurity. Ninety-two per cent of people that entered the poultry barns (46/50) used one or more biosecurity practices, whereas 81% of people (48/59) that did not enter the poultry barns used one or more biosecurity practices. Because our study documented farm visitors who did not use any biosecurity practices and moved between commercial poultry farms, we suggest that rapid trace-out of human movements is as important as containment zoning to limiting disease spread during an outbreak of highly pathogenic AI in Ontario., (© 2011 Blackwell Verlag GmbH.)

This paper explores methods for describing the dynamics of early epidemic spread and the clustering of infected cases in space and time when an underlying contact network structure is influencing disease spread. A novel method of describing an epidemic is presented that applies social network analysis to characterise the importance of both spatial location and contact network position. This method enables the development of a model of how these clusters formed, incorporating spatial clustering and contact network topology. Based on data from the first 30 days of the 2007 equine influenza outbreak in Australia, clusters of infected premises (IPs) were identified and delineated using social network analysis to integrate contact-tracing and spatial relationships. Clusters identified by this approach were compared to those detected using the space-time scan statistic to analyse the same data. To further investigate the importance of network and spatial location in epidemic spread, kriging by date of onset of clinical signs was used to model the spatio-temporal spread without reference to underlying contact network structure. Leave-one-out cross-validation was used to derive a summary estimate of the accuracy of the kriged surface. Observations poorly explained by the kriged surface were identified, and their position within the contact network was explored to determine if they could be better explained through analysis of the underlying contact network. The contact network was found to lie at the core of a combined network model of spread, with infected horse movements connecting spatial clusters of infected premises. Kriging was imprecise in describing the pattern of spread during this early phase of the outbreak (explaining only 13% of the variation in date of onset of IPs), because early dissemination was dominated by network-based spread. Combined analysis of spatial and contact network data demonstrated that over the first 30 days of this outbreak local spread emanated outwards from the small number of infected premises in the contact network, up to a distance of around 15km. Consequently, when a contact network structure underlies epidemic spread, we recommend applying a method of spatial analysis that incorporates the network component of disease spread. Linking the spatial and network analysis of epidemics facilitates inference of the methods of disease transmission, providing a description of the sequence of spatial cluster formation., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Aim: To determine, for a variety of environmental conditions, how long Mycobacterium bovis might remain viable inside the carcass of a brushtail possum (Trichosurus vulpecula) that died of bovine tuberculosis (Tb), and to measure the rate of contact between free-ranging possums and possum carcasses., Methods: Lesions of M. bovis were simulated by inoculating excised spleens weighing 0.5-1 g with 0.2 mL liquid culture containing approximately 5 x 10(7) cfu M. bovis/mL. Simulated lesions were inserted into possum carcasses (n=48) at the peripheral lymph nodes. Carcasses were placed in the field at two sites (a tussock grassland and a podocarp-broadleaved forest site) and in two seasons (summer and winter) for up to 62 days. Survival rates of M. bovis were estimated by sampling the simulated lesions over time, and culturing the recovered lesion to determine if any viable M. bovis bacteria were present. The time taken for a free-ranging possum to first encounter a dead possum in its home range was estimated by live-trapping possums and fitting them with proximity loggers (n=13). A 'contact' was recorded if these possums came within 40-50 cm of proximity loggers fitted to possum carcasses., Results: There were strong seasonal and site effects in the survival rate of M. bovis in possum carcasses. In the grassland habitat, no viable bacilli were cultured from any carcass after 3 days in summer, whereas in winter all samples were culture-positive for the first 20 days, and some were still positive after 27 days. The survival rates for forest habitat were intermediate between the results for grassland, and there were no culture-positive carcasses after 9 days in summer or 27 days in winter. In summer, infected carcasses (n=6) were first encountered by possums a mean 1.9 (range 0.4-6.7) days after placement., Conclusions: Possum carcasses were contacted by free-ranging possums within the period that viable M. bovis were shown to survive in a carcass. The risk of such infection is likely to be most significant in winter or in areas with microhabitats where the survival of M. bovis is high. However, the generally low survival rate of M. bovis in possum carcasses and the low frequency of possum-to-carcass contacts indicate this route of transmission alone could not maintain Tb in a possum population.

Frontline farm workers and veterinary-policy-makers are arguably in the best positions to influence prevention, detection, and preparedness-for-control of farm animal diseases. It is important that such individuals make biologically sound decisions concerning the daily management and regulation of the health of animals. Such decisions should be based on a good understanding of key principles of disease spread and control. This paper summarises these principles, as described in previous publications, into simple models. These models may be used to communicate concepts to readers who may not have time to study more complex models. These models illustrate the relationship between the development of new disease cases (from existing cases, i.e., the reproductive ratio R) and (i) the duration of the period during which existing cases are available as infectious, (ii) contact rates, (iii) transmission rates and (iv) susceptibility. Understanding these concepts through models has great utility, facilitating better decisions for disease prevention, detection and preparedness-for-control, before an outbreak becomes unmanageable. These basic concepts apply to all animal species, including humans.

The aim of this study was to identify risk factors for bovine tuberculosis (TB) in a free-roaming, capture-mark-recapture monitored possum Trichosurus vulpecula population in a 22-ha study site at Castlepoint, New Zealand from 1 April 1989 to 31 March 1994. A matched case-control design was used to evaluate the influence of sex, habitat and contact opportunities on TB risk. Cases comprised possums identified as TB-positive throughout the study period. Controls were selected from the group of possums that were captured and showed no clinical signs of TB throughout the study period. Measures derived from a social network analysis of possum capture locations such as degree, clustering coefficient (CC) and betweenness were used to represent potential contact opportunities among possums. Network analysis measures recorded for individual possums in the 12-month period before a diagnosis of TB were evaluated in a conditional logistic regression model. We found no evidence of an association between case status and the total number of possums with which there was potential contact (degree) (P=0.5). The odds of cases being exposed to unit increases in the number of TB-positive contacts was 2.50 (95% CI 1.24-5.05; P<0.01) times that of controls. This effect was conditional on the total number of potential contacts made, with a negative interaction with increasing degree. These findings indicate that potential contact with TB-positive possums increases the odds of disease whereas potential contact with large numbers of possums does not. This suggests that multiple contacts with TB-positive possum(s) are necessary for transmission of TB and this is more likely to occur in networks that are smaller. We challenge the hypothesis that contact with large numbers of individuals increases the probability of becoming TB infected and argue that individual contact behaviour is a determinant of the creation of TB foci within free-living possum populations., (© 2011 Elsevier B.V. All rights reserved.)

Until August 2007, Australia was one of only three countries internationally recognised to be free of equine influenza (EI). This report documents the diagnosis of the first cases of EI in Australian horses and summarises the investigations that took place over the next 5 days. During that time, a multifocal outbreak was identified across eastern New South Wales and south-eastern Queensland. The use of an influenza type A pan-reactive real-time reverse transcription polymerase chain reaction allowed rapid confirmation of suspect cases of EI., (© 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.)

Sweden has been considered free from bovine tuberculosis (BTB) since 1958. In 1987 an infected consignment of farmed deer was imported to Sweden and in 1991 the first infected deer was identified. Despite a thorough trace back investigation, all deer originating from the infected consignment could not be traced. Therefore a national control programme for BTB in farmed deer was implemented. At present the control programme is in its final stage and all deer holdings that have not obtained BTB-free status are put under restrictions. This study aimed to determine the probability that the Swedish farmed deer population is free from BTB using methods that allow analysis of non-structured data, i.e. results from meat inspection, necropsies and tuberculin testing. Surveillance data from 1994 to October 2006 from farmed deer affiliated to the voluntary control programme were analysed using the model described in Martin et al. (2007a). The model was adjusted to allow the within-herd design prevalence to be defined as one infected deer per herd and the between-herd design prevalence to be defined as one infected deer herd in the country. Depending on the chosen within-herd design prevalence: 1, 2, 3 or 4 infected deer per herd or 5% infected deer per herd, the probability of freedom from BTB infection in the Swedish farmed deer population varied between 87% and 97%. Based on the obtained results, it can be concluded, with high confidence, that the Swedish farmed deer population is free from M. bovis.

All the Irish cattle herds considered "clear" of bovine tuberculosis (BTB) having a single animal with a tuberculous lesion at slaughter during 2003 were identified. We performed a descriptive and logistic regression analysis to investigate whether selected risk factors had an association with the result of the herd test immediately after the tuberculous lesion was found ("Factory Lesion Test", FLT). At the FLT, only 19.7% (n=338) of these 1713 herds had 1 or more standard reactors. The lesioned animal was home-bred in 46% of the "source" herds; these herds had an increased risk (23.4%) of having at least 1 standard reactor animal relative to herds with a purchased-lesioned animal (16.6%) (RR=1.41). Our logistic models identified a number of important risk factors; two that appeared most important in predicting the FLT outcome were the time spent (residency) by the lesioned animal in the "source" herd, and the presence, or not, of the lesioned animal in a previous BTB episode in either the "source" herd, or the seller's herd in the case the lesioned animal was purchased. Our models fit the data well based on the Hosmer-Lemeshow test, however their sensitivity and specificity were very low (57% and 61% respectively). Surveillance of the cattle population for BTB using lesions found at slaughter is an essential component of an overall control program. Nonetheless, due to the poor predictability of the variables we measured, complete herd investigations are needed to help explain the FLT outcome of a herd.

Global demands for increased food safety and quality assurance programmes, increased global competition, changing government rules and regulations, political and trade barriers, bioterrorism, and identity preservation requirements in global markets are affecting the world's food supply chain. To satisfy changing market demands, all suppliers in the food supply chain must adaptto these global issues. Total asset visibility must be maintained in production, in process, in storage, and in transit.

The objective of this study was to develop a suitable combination consisting of synthetic peptides, carrier protein and adjuvant for immunological labelling of pigs. Specific antibody titres were evaluated by ELISA technique. From 9 peptides 4 were excluded from following investigations showing cross reactivity or low immunogenic effects, sufficient anti-peptide titres were achieved by 5 peptides. Labelling control is possible after 7 days at the earliest and can be used for the whole fattening period after single immunization using an effective carrier-adjuvant-combination. Mixing of peptides in one labelling dose had no negative influence on titres against single peptides. Different combinations of 4 carriers (keyhole limpet haemocyanin (KLH), palmitic-acid-3-cystein-acid (Pam3Cys), palmitic acid (Pam) and dextran) and 4 adjuvants (Montanide IMS 1313, Montanide ISA 25, Quil A and Diluvac forte) were tested. Optimal labelling could be seen by combination of 50 nmol peptide, KLH as carrier and Montanide IMS 1313 as adjuvant. Generally after booster injection titres were higher, however, a booster dose was not necessary using most effective adjuvants. A less immunogenic, but cost effective alternative for short time labelling (7 weeks) was a peptide-Pam3Cys-conjugate (75 nmol) combined with Quil A as an adjuvant (2 mg/ml). Immunological labelling of pigs is recommended as a good method for tracing back the origin of animals and meat products. It may be also used for vaccine labelling to prove vaccination of pigs.

The case-reproduction ratio for the spread of an infectious disease is a critically important concept for understanding dynamics of epidemics and for evaluating impact of control measures on spread of infection. Reliable estimation of this ratio is a problem central to epidemiology and is most often accomplished by fitting dynamic models to data and estimating combinations of parameters that equate to the case-reproduction ratio. Here, we develop a novel parameter-free method that permits direct estimation of the history of transmission events recoverable from detailed observation of a particular epidemic. From these reconstructed 'epidemic trees', case-reproduction ratios can be estimated directly. We develop a bootstrap algorithm that generates percentile intervals for these estimates that shows the procedure to be both precise and robust to possible uncertainties in the historical reconstruction. Identifying and 'pruning' branches from these trees whose occurrence might have been prevented by implementation of more stringent control measures permits estimation of the possible efficacy of these alternative measures. Examination of the cladistic structure of these trees as a function of the distance of each case from its infection source reveals useful insights about the relationship between long-distance transmission events and epidemic size. We demonstrate the utility of these methods by applying them to data from the 2001 foot-and-mouth disease outbreak in the UK.

A study on contacts between livestock holdings was conducted in a geographically defined area of 4 by 6 km in the Netherlands. The farmers were asked to record all contact on and off farm during a period of 2 weeks. The number of contacts in the 2 week period was high, on average 91.8 contacts per farm. The risk of spreading foot-and-mouth disease on or off the farm was greater for cattle farms than for swine farms. Relatively more people had contact with the animals while visiting cattle farms, thereby causing the higher risk. Most contacts occurred over short distances. Almost 50% of the contacts were within the research area. This finding confirms the importance of restricted areas around farms with foot-and-mouth disease infections.

Bovine tuberculosis was eradicated from Sweden after a programme lasting many years. By 1991, no tuberculosis in wildlife had been discovered for 50 years and the last case in cattle had occurred 13 years before. In 1991, the disease was identified in a herd of farmed fallow deer (Dama dama) and over the next three years nine other infected herds were identified. Investigation revealed that all the infected deer were either deer that had been imported into Sweden from the United Kingdom in 1987 or had been in contact with them. Restriction fragment analysis of eight isolates of Mycobacterium bovis from five of the herds showed that the isolates had identical patterns of DNA fragments, which indicated a common source of infection. Among more than 800 isolates of M bovis that have been analysed, these patterns were identical to those of only two previous isolates, both of which came from British deer. These results indicate that the eight Swedish strains of M bovis and the two British strains may have a common source of infection.