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  • 1.
    Berndtson, E.
    et al.
    Department of Food Hygiene, Faculty of Veterinary Medicine, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Emanuelson, U.
    Swedish Association for Livestock Breeding and Production, Eskilstuna, Sweden .
    Engvall, A.
    Department of Epizootiology, National Veterinary Institute, Uppsala, Sweden .
    Danielsson-Tham, Marie-Louise
    Department of Food Hygiene, Faculty of Veterinary Medicine, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    A 1-year epidemiological study of campylobacters in 18 Swedish chicken farms1996Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 26, nr 3-4, s. 167-185Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Broiler chickens are often intestinal carriers of Campylobacter. During processing, Campylobacter may be spread over the carcass. Thus, undercooked chicken meat, or other foods contaminated by raw chicken can act as a source of infection to humans. This study was conducted to identify risk factors for chicken flocks being colonized with Campylobacter. Eighteen chicken farms with altogether 62 chicken compartments were studied for 1 year with visits during each growing period and sampling of chicken caecal contents at slaughter. Four to six subsequent flocks were raised in each compartment during the study. A detailed questionnaire was used to record farm parameters such as building materials, feed and water equipment, hygiene and management routines. Campylobacter prevalence varied between farms, between growing periods within the farms and also during the year, with lowest prevalence during the spring. Campylobacters were isolated from 27% out of 287 flocks. Only two farms were negative at all samplings. Often the flock following a positive flock in a compartment was negative, indicating that normal cleaning and disinfecting routines are sufficient for eliminating the bacteria from the house. Usually only one serotype was found in each positive flock. Campylobacter occurrence increased with the age of the chickens at slaughter, and also with flock size.

    Univariable chi-square tests were done of the association between possible risk factors and Campylobacter prevalence. Factors associated with higher Campylobacter prevalence in flocks were lack of or diffuse hygiene barriers, increasing flock size, increasing age at slaughter, short vs. long empty periods, wet litter beds, other poultry nearby or staff handling other poultry, flocks divided before slaughter, staff loading to slaughter at several farms and occurrence of mice. Under Swedish conditions, water does not seem to be a source of infection for chickens. Origin and handling of day-old chickens, feed additives, houses and litter were not associated with higher Campylobacter prevalence.

  • 2. Bett, B
    et al.
    Kiunga, P
    Gachohi, J
    Sindato, C
    Mbotha, D
    Robinson, T
    Lindahl, J
    Grace, D
    Effects of climate change on the occurrence and distribution of livestock diseases.2017Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 137, nr Pt B, s. 119-129, artikkel-id S0167-5877(16)30631-6Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The planet's mean air and ocean temperatures have been rising over the last century because of increasing greenhouse gas (GHG) emissions. These changes have substantial effects on the epidemiology of infectious diseases. We describe direct and indirect processes linking climate change and infectious diseases in livestock with reference to specific case studies. Some of the studies are used to show a positive association between temperature and expansion of the geographical ranges of arthropod vectors (e.g. Culicoides imicola, which transmits bluetongue virus) while others are used to illustrate an opposite trend (e.g. tsetse flies that transmit a range of trypanosome parasites in sub-Saharan Africa). We further describe a positive association between extreme events: droughts and El Niño/southern oscillation (ENSO) weather patterns and Rift Valley fever outbreaks in East Africa and some adaptation practices used to mitigate the impacts of climate change that may increase risk of exposure to infectious pathogens. We conclude by outlining mitigation and adaptation measures that can be used specifically in the livestock sector to minimize the impacts of climate change-associated livestock diseases.

  • 3.
    Dórea, Fernanda C.
    et al.
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Vial, Flavie
    Epi-Connect, Skogås, Sweden.
    Hammar, Karl
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten. Department of Computer Science and Informatics, Jönköping University, Sweden.
    Lindberg, Ann
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Lambrix, Patrick
    Linköpings universitet, Institutionen för datavetenskap, Databas och informationsteknik. Linköpings universitet, Tekniska fakulteten.
    Blomqvist, Eva
    Linköpings universitet, Institutionen för datavetenskap, Interaktiva och kognitiva system. Linköpings universitet, Tekniska fakulteten.
    Revie, Crawford W.
    Atlantic Veterinary College, University of Prince Edward Island, Canada.
    Drivers for the development of an Animal Health Surveillance Ontology (AHSO)2019Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 166, nr 1, s. 39-48Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields of animal and public health, as well as computer scientists from the field of information management, have led to the conclusion that a major component of any solution will involve the adoption of ontologies. Here we describe the advantages of such an approach, and the steps taken to set up the Animal Health Surveillance Ontological (AHSO) framework. The AHSO framework is modelled in OWL, the W3C standard Semantic Web language for representing rich and complex knowledge. We illustrate how the framework can incorporate knowledge directly from domain experts or from data-driven sources, as well as by integrating existing mature ontological components from related disciplines. The development and extent of AHSO will be community driven and the final products in the framework will be open-access.

  • 4.
    Dórea, Fernanda C.
    et al.
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Vial, Flavie
    Epi-Connect, Skogås, Sweden.
    Hammar, Karl
    Högskolan i Jönköping, Tekniska Högskolan, JTH, Datateknik och informatik, JTH, Jönköping AI Lab (JAIL). Department of Computer and Information Science, Linköping University, Sweden.
    Lindberg, Ann
    Department of Disease Control and Epidemiology, National Veterinary Institute, Sweden.
    Lambrix, Patrick
    Department of Computer and Information Science, Linköping University, Sweden.
    Blomqvist, Eva
    Department of Computer and Information Science, Linköping University, Sweden.
    Revie, Crawford W.
    Atlantic Veterinary College, University of Prince Edward Island, Canada.
    Drivers for the development of an Animal Health Surveillance Ontology (AHSO)2019Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 166, s. 39-48Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Comprehensive reviews of syndromic surveillance in animal health have highlighted the hindrances to integration and interoperability among systems when data emerge from different sources. Discussions with syndromic surveillance experts in the fields of animal and public health, as well as computer scientists from the field of information management, have led to the conclusion that a major component of any solution will involve the adoption of ontologies. Here we describe the advantages of such an approach, and the steps taken to set up the Animal Health Surveillance Ontological (AHSO) framework. The AHSO framework is modelled in OWL, the W3C standard Semantic Web language for representing rich and complex knowledge. We illustrate how the framework can incorporate knowledge directly from domain experts or from data-driven sources, as well as by integrating existing mature ontological components from related disciplines. The development and extent of AHSO will be community driven and the final products in the framework will be open-access.

  • 5. Espetvedt, Mari. N.
    et al.
    Wolff, Cecilia
    Rintakoski, Simo
    Lind, A.
    RISE, SP – Sveriges Tekniska Forskningsinstitut, JTI Institutet för Jordbruks- och Miljöteknik.
    Österås, O.
    Completeness of metabolic disease recordings in Nordic national databases for dairy cows.2012Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 105, s. 25-37Artikkel i tidsskrift (Fagfellevurdert)
  • 6.
    Frossling, Jenny
    et al.
    SVA, Sweden Swedish University of Agriculture Science, Sweden .
    Ohlson, Anna
    SVA, Sweden Swedish University of Agriculture Science, Sweden .
    Bjorkman, Camilla
    Swedish University of Agriculture Science, Sweden .
    Håkansson, Nina
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Noremark, Maria
    SVA, Sweden .
    Application of network analysis parameters in risk-based surveillance - Examples based on cattle trade data and bovine infections in Sweden2012Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 105, nr 3, s. 202-208Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Financial resources may limit the number of samples that can be collected and analysed in disease surveillance programmes. When the aim of surveillance is disease detection and identification of case herds, a risk-based approach can increase the sensitivity of the surveillance system. In this paper, the association between two network analysis measures, i.e. in-degree and ingoing infection chain, and signs of infection is investigated. It is shown that based on regression analysis of combined data from a recent cross-sectional study for endemic viral infections and network analysis of animal movements, a positive serological result for bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) is significantly associated with the purchase of animals. For BCV, this association was significant also when accounting for herd size and regional cattle density, but not for BRSV. Examples are given for different approaches to include cattle movement data in risk-based surveillance by selecting herds based on network analysis measures. Results show that compared to completely random sampling these approaches increase the number of detected positives, both for BCV and BRSV in our study population. It is concluded that network measures for the relevant time period based on updated databases of animal movements can provide a simple and straight forward tool for risk-based sampling.

  • 7.
    Frössling, Jenny
    et al.
    Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden / Department of Animal Environment and Health, Swedish University of Agricultural Sciences, Skara, Sweden.
    Ohlson, Anna
    Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden / Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Björkman, Camilla
    Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Håkansson, Nina
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi. Division of Theoretical Biology, IFM Theory and Modelling, Linköping University, Linköping, Sweden.
    Nöremark, Maria
    Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden.
    Application of network analysis parameters in risk-based surveillance - Examples based on cattle trade data and bovine infections in Sweden2012Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 105, nr 3, s. 202-208Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Financial resources may limit the number of samples that can be collected and analysed in disease surveillance programmes. When the aim of surveillance is disease detection and identification of case herds, a risk-based approach can increase the sensitivity of the surveillance system. In this paper, the association between two network analysis measures, i.e. ‘in-degree’ and ‘ingoing infection chain’, and signs of infection is investigated. It is shown that based on regression analysis of combined data from a recent cross-sectional study for endemic viral infections and network analysis of animal movements, a positive serological result for bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) is significantly associated with the purchase of animals. For BCV, this association was significant also when accounting for herd size and regional cattle density, but not for BRSV. Examples are given for different approaches to include cattle movement data in risk-based surveillance by selecting herds based on network analysis measures. Results show that compared to completely random sampling these approaches increase the number of detected positives, both for BCV and BRSV in our study population. It is concluded that network measures for the relevant time period based on updated databases of animal movements can provide a simple and straight forward tool for risk-based sampling.

  • 8.
    Gorsich, Erin E.
    et al.
    Colorado State Univ, CO 80523 USA.
    McKee, Clifton D.
    Colorado State Univ, CO 80523 USA.
    Grear, Daniel A.
    USDA APHIS Vet Serv, CO USA.
    Miller, Ryan S.
    USDA APHIS Vet Serv, CO USA.
    Portacci, Katie
    USDA APHIS Vet Serv, CO USA.
    Lindström, Tom
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska fakulteten.
    Webb, Colleen T.
    Colorado State Univ, CO 80523 USA; Colorado State Univ, CO 80523 USA.
    Model-guided suggestions for targeted surveillance based on cattle shipments in the US2018Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 150, s. 52-59Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Risk-based sampling is an essential component of livestock health surveillance because it targets resources towards sub-populations with a higher risk of infection. Risk-based surveillance in U.S. livestock is limited because the locations of high-risk herds are often unknown and data to identify high-risk herds based on shipments are often unavailable. In this study, we use a novel, data-driven network model for the shipments of cattle in the U.S. (the U.S. Animal Movement Model, USAMM) to provide surveillance suggestions for cattle imported into the U.S. from Mexico. We describe the volume and locations where cattle are imported and analyze their predicted shipment patterns to identify counties that are most likely to receive shipments of imported cattle. Our results suggest that most imported cattle are sent to relatively few counties. Surveillance at 10 counties is predicted to sample 22-34% of imported cattle while surveillance at 50 counties is predicted to sample 43%-61% of imported cattle. These findings are based on the assumption that USAMM accurately describes the shipments of imported cattle because their shipments are not tracked separately from the remainder of the U.S. herd. However, we analyze two additional datasets - Interstate Certificates of Veterinary Inspection and brand inspection data - to ensure that the characteristics of potential post-import shipments do not change on an annual scale and are not dependent on the dataset informing our analyses. Overall, these results highlight the utility of USAMM to inform targeted surveillance strategies when complete shipment information is unavailable.

  • 9.
    Lindström, Tom
    et al.
    IFM Theory and Modelling, Linköping University.
    Sisson, Scott A.
    School of Mathematics and Statistics, University of New South Wales, Sydney.
    Nöremark, Maria
    Department of Disease Control and Epidemiology, SVA, National Veterinary Institute.
    Jonsson, Annie
    Högskolan i Skövde, Forskningscentrum för Systembiologi. Högskolan i Skövde, Institutionen för vård och natur.
    Wennergren, Uno
    IFM Theory and Modelling, Linköping University.
    Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling2009Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 91, nr 2-4, s. 85-94Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

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

    We found that the mixture model was a much better model for the data analyzed. Also, the network measures showed that the models differed considerably in predictions of contact structures, which is expected to be important for disease spread dynamics. We conclude that a model with contacts being both dependent on, and independent of, distance was preferred for modeling the example animal movement contact data.

  • 10.
    Lindström, Tom
    et al.
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Sisson, Scott A.
    School of Mathematics and Statistics, University of New South Wales, Sydney 2052, Australia.
    Nöremark, Maria
    Department of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden.
    Jonsson, Annie
    Research Centre of Systems Biology, Ecological Modelling, University of Skövde, 541 28 Skövde, Sweden.
    Wennergren, Uno
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Estimation of distance related probability of animal movements between holdings and implications for disease spread modeling2009Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 91, nr 2-4, s. 85-94Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

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

  • 11.
    Lindström, Tom
    et al.
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Sisson, Scott A.
    School of Mathematics and Statistics, University of New South Wales, Sydney 2052, Australia.
    Stenberg Lewerin, Susanna
    Department of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden.
    Wennergren, Uno
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Bayesian analysis of animal movements related to factors at herdand between herd levels: Implications for disease spread modeling2011Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 98, nr 4, s. 230-242Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    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 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 farms. 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.

  • 12.
    Lindström, Tom
    et al.
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Sisson, Scott A
    School of Mathematics and Statistics, University of New South Wales, Sydney 2052, Australia.
    Stenberg Lewerin, Susanna
    Department of Disease Control and Epidemiology, SVA, National Veterinary Institute, 751 89 Uppsala, Sweden.
    Wennergren, Uno
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska högskolan.
    Estimating animal movement contacts between holdings of different production types2010Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 95, nr 1-2, s. 23-31Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Animal movement poses a great risk for disease transmission between holdings. Heterogeneous contact patterns are known to influence the dynamics of disease transmission and should be included in modeling. Using pig movement data from Sweden as an example, we present a method for quantification of between holding contact probabilities based on different production types. The data contained seven production types: Sow pool center, Sow pool satellite, Farrow-to-finish, Nucleus herd, Piglet producer, Multiplying herd and Fattening herd. The method also estimates how much different production types will determine the contact pattern of holdings that have more than one type. The method is based on Bayesian analysis and uses data from central databases of animal movement. Holdings with different production types are estimated to vary in the frequency of contacts as well as in what type of holding they have contact with, and the direction of the contacts. Movements from Multiplying herds to Sow pool centers, Nucleus herds to other Nucleus herds, Sow pool centers to Sow pool satellites, Sow pool satellites to Sow pool centers and Nucleus herds to Multiplying herds were estimated to be most common relative to the abundance of the production types. We show with a simulation study that these contact patterns may also be expected to result in substantial differences in disease transmission via animal movements, depending on the index holding. Simulating transmission for a 1 year period showed that the median number of infected holdings was 1 (i.e. only the index holding infected) if the infection started at a Fattening herd and 2161 if the infection started on a Nucleus herd. We conclude that it is valuable to include production types in models of disease transmission and the method presented in this paper may be used for such models when appropriate data is available. We also argue that keeping records of production types is of great value since it may be helpful in risk assessments.

  • 13.
    Nöremark, Maria
    et al.
    SVA, National Veterinary Institute, Department of Disease Control and Epidemiology, 751 89 Uppsala, Sweden / Department of Clinical Sciences, Swedish University of Agricultural Sciences, Box 7054, 750 09 Uppsala, Sweden.
    Håkansson, Nina
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Sternberg Lewerin, Susanna
    SVA, National Veterinary Institute, Department of Disease Control and Epidemiology, 751 89 Uppsala, Sweden.
    Lindberg, Ann
    SVA, National Veterinary Institute, Department of Disease Control and Epidemiology, 751 89 Uppsala, Sweden.
    Jonsson, Annie
    Högskolan i Skövde, Institutionen för vård och natur. Högskolan i Skövde, Forskningscentrum för Systembiologi.
    Network analysis of cattle and pig movements in Sweden: Measures relevant for disease control and risk based surveillance2011Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 99, nr 2-4, s. 78-90Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Registration ofcattle and pigmovements is mandatory in Sweden and all registered movements between farms in the years 2006–2008 were investigated using network analysis. The networks were analysed as monthly and yearly networks, separately per species and with the two species together. Measures that have been previously discussed in relation to outbreaks and disease control were calculated; moreover a measure of the ingoing infection chain was constructed.The ingoing infection chain captures in going contacts through other holdings, taking the temporal aspect and sequence of the movements into account. The distribution of the contacts among the holdings was skewed.Many farms had few or no contacts, while others had many, a pattern which has also been described from other countries. The cattle network and the combined network showed a recurring seasonal pattern, while this was not seen in the pig network.The in-degree was not equivalent to the ingoing infection chain; there were holdings with limited direct contacts, but a large number of indirect contacts.The ingoing infection chain could be a useful measure when setting up strategies for disease control and for risk based surveillance as it identifies holdings with many contacts through live animal movements and thus at potentially higher risk for introduction of contagious diseases.

  • 14.
    Svensson, C.
    et al.
    Swedish Univ Agr Sci, Dept Clin Sci, Uppsala, Sweden.
    Alvasen, K.
    Swedish Univ Agr Sci, Dept Clin Sci, Uppsala, Sweden.
    Eldh, Ann Catrine
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för folkhälso- och vårdvetenskap, Hälso- och sjukvårdsforskning.
    Frossling, J.
    Natl Vet Inst, Dept Dis Control & Epidemiol, Uppsala, Sweden;Swedish Univ Agr Sci, Dept Anim Environm & Hlth, Skara, Sweden.
    Lomander, H.
    Swedish Board Agr, Dist Vet Org, Tibro, Sweden.
    Veterinary herd health management: Experience among farmers and farm managers in Swedish dairy production2018Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 155, s. 45-52Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A preventive herd health approach will most likely reduce incidences of clinical and subclinical disease. Swedish veterinary organizations offer specific veterinary herd health management (HHM) programs, but these services are not used to a large extent. The aim of this study was to investigate dairy farmers' experience of HHM and the conditions for collaboration with veterinarians in HHM. Six focus group discussions were conducted in March 2015 in West Sweden. In total, 33 dairy farmers participated. The recordings were transcribed and coded using thematic analysis, and the transcripts were reviewed to identify potential factors indicating barriers for farmers to engage a veterinarian in HHM. The participants reported HHM to be important, but they had difficulty defining the actions included in the concept. They described a wide range of their work duties as preventive. The farmers' list of potential contributions by the veterinarians in HHM was strikingly short compared to the considerable number of preventive measures they performed themselves. Four main obstacles for farmers and farm managers to engage a veterinarian in HHM on their farm were identified in the analysis: "costs", "veterinary knowledge, skills, and organization", "farmer attitudes", and "veterinarian-farmer relationships". Costs were proposed as the main reason against engaging a veterinarian in HHM and included a high veterinary bill, low cost-benefit of veterinary services, and high costs to implement advice. Poor veterinary competence in HHM and poor knowledge about effective measures, practical farming, and farm economics were other important obstacles. Veterinarians were perceived to insufficiently describe their services and their benefits, and several participants felt they had never been offered veterinary HHM. Although veterinary HHM may be initiated by the farmer, the participants expected the veterinarian to have special responsibility for the initiation. A firm trust between farmer, staff, and veterinarian was considered crucial for veterinary HHM, but such trust takes a long time to build and can easily be disrupted by, for example, a veterinarian's poor communication skills or lack of time. Our findings suggest that Swedish dairy farmers and herd managers find disease prevention important and that they perform a wide range of tasks to prevent disease in their animals. However, they do not see what role the veterinarian can play, and veterinarians were mainly associated with treating unhealthy cows. In order to increase the use of veterinary HHM programs the services and potential benefits of such programs need to be communicated more proactively.

  • 15.
    Svensson, Catarina
    et al.
    Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Alvåsen, Karin
    Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Eldh, Ann Catrine
    Division of Nursing, Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden.
    Frössling, Jenny
    Department of Disease Control and Epidemiology, National Veterinary Institute, Uppsala, Sweden; Department of Animal Environment and Health, Swedish University of Agricultural Sciences, Skara, Sweden.
    Lomander, H.
    District Veterinary Organization, Swedish Board of Agriculture, Tibro, Sweden.
    Veterinary herd health management: Experience among farmers and farm managers in Swedish dairy production2018Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 155, s. 45-52Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A preventive herd health approach will most likely reduce incidences of clinical and subclinical disease. Swedish veterinary organizations offer specific veterinary herd health management (HHM) programs, but these services are not used to a large extent.

    The aim of this study was to investigate dairy farmers’ experience of HHM and the conditions for collaboration with veterinarians in HHM.

    Six focus group discussions were conducted in March 2015 in West Sweden. In total, 33 dairy farmers participated. The recordings were transcribed and coded using thematic analysis, and the transcripts were reviewed to identify potential factors indicating barriers for farmers to engage a veterinarian in HHM. The participants reported HHM to be important, but they had difficulty defining the actions included in the concept. They described a wide range of their work duties as preventive. The farmers’ list of potential contributions by the veterinarians in HHM was strikingly short compared to the considerable number of preventive measures they performed themselves. Four main obstacles for farmers and farm managers to engage a veterinarian in HHM on their farm were identified in the analysis: “costs”, “veterinary knowledge, skills, and organization”, “farmer attitudes”, and “veterinarian-farmer relationships”. Costs were proposed as the main reason against engaging a veterinarian in HHM and included a high veterinary bill, low cost-benefit of veterinary services, and high costs to implement advice. Poor veterinary competence in HHM and poor knowledge about effective measures, practical farming, and farm economics were other important obstacles. Veterinarians were perceived to insufficiently describe their services and their benefits, and several participants felt they had never been offered veterinary HHM. Although veterinary HHM may be initiated by the farmer, the participants expected the veterinarian to have special responsibility for the initiation. A firm trust between farmer, staff, and veterinarian was considered crucial for veterinary HHM, but such trust takes a long time to build and can easily be disrupted by, for example, a veterinarian’s poor communication skills or lack of time.

    Our findings suggest that Swedish dairy farmers and herd managers find disease prevention important and that they perform a wide range of tasks to prevent disease in their animals. However, they do not see what role the veterinarian can play, and veterinarians were mainly associated with treating unhealthy cows. In order to increase the use of veterinary HHM programs the services and potential benefits of such programs need to be communicated more proactively.

  • 16.
    Webb, Colleen T.
    et al.
    Colorado State University, CO 80523 USA.
    Ferrari, Matthew
    Penn State University, PA 16802 USA.
    Lindström, Tom
    Linköpings universitet, Institutionen för fysik, kemi och biologi, Teoretisk Biologi. Linköpings universitet, Tekniska fakulteten. Colorado State University, CO 80523 USA.
    Carpenter, Tim
    Massey University, New Zealand.
    Duerr, Salome
    University of Bern, Switzerland.
    Garner, Graeme
    Department Agriculture, Australia.
    Jewell, Chris
    Massey University, Palmerston North, New Zealand.
    Stevenson, Mark
    University of Melbourne, Australia.
    Ward, Michael P.
    University of Sydney, Australia.
    Werkman, Marleen
    CVI, Netherlands.
    Backer, Jantien
    CVI, Netherlands.
    Tildesley, Michael
    University of Warwick, England.
    Ensemble modelling and structured decision-making to support Emergency Disease Management2017Inngår i: Preventive Veterinary Medicine, ISSN 0167-5877, E-ISSN 1873-1716, Vol. 138, s. 124-133Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Epidemiological models in animal health are commonly used as decision-support tools to understand the impact of various control actions on infection spread in susceptible populations. Different models contain different assumptions and parameterizations, and policy decisions might be improved by considering outputs from multiple models. However, a transparent decision-support framework to integrate outputs from multiple models is nascent in epidemiology. Ensemble modelling and structured decision-making integrate the outputs of multiple models, compare policy actions and support policy decision-making. We briefly review the epidemiological application of ensemble modelling and structured decision-making and illustrate the potential of these methods using foot and mouth disease (FMD) models. In case study one, we apply structured decision-making to compare five possible control actions across three FMD models and show which control actions and outbreak costs are robustly supported and which are impacted by model uncertainty. In case study two, we develop a methodology for weighting the outputs of different models and show how different weighting schemes may impact the choice of control action. Using these case studies, we broadly illustrate the potential of ensemble modelling and structured decision-making in epidemiology to provide better information for decision-making and outline necessary development of these methods for their further application. Crown Copyright (C) 2017 Published by Elsevier B.V. All rights reserved.

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