AusVet Animal Health Services

Wentworth Falls, Australia

AusVet Animal Health Services

Wentworth Falls, Australia

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Brookes V.J.,University of Sydney | Hernandez-Jover M.,Charles Sturt University | Cowled B.,AusVet Animal Health Services | Holyoake P.K.,Australian Department of Primary Industries and Fisheries | Ward M.P.,University of Sydney
Preventive Veterinary Medicine | Year: 2014

Diseases that are exotic to the pig industry in Australia were prioritised using a multi-criteria decision analysis framework that incorporated weights of importance for a range of criteria important to industry stakeholders. Measurements were collected for each disease for nine criteria that described potential disease impacts. A total score was calculated for each disease using a weighted sum value function that aggregated the nine disease criterion measurements and weights of importance for the criteria that were previously elicited from two groups of industry stakeholders. One stakeholder group placed most value on the impacts of disease on livestock, and one group placed more value on the zoonotic impacts of diseases. Prioritisation lists ordered by disease score were produced for both of these groups. Vesicular diseases were found to have the highest priority for the group valuing disease impacts on livestock, followed by acute forms of African and classical swine fever, then highly pathogenic porcine reproductive and respiratory syndrome. The group who valued zoonotic disease impacts prioritised rabies, followed by Japanese encephalitis, Eastern equine encephalitis and Nipah virus, interspersed with vesicular diseases. The multi-criteria framework used in this study systematically prioritised diseases using a multi-attribute theory based technique that provided transparency and repeatability in the process. Flexibility of the framework was demonstrated by aggregating the criterion weights from more than one stakeholder group with the disease measurements for the criteria. This technique allowed industry stakeholders to be active in resource allocation for their industry without the need to be disease experts. We believe it is the first prioritisation of livestock diseases using values provided by industry stakeholders. The prioritisation lists will be used by industry stakeholders to identify diseases for further risk analysis and disease spread modelling to understand biosecurity risks to this industry. © 2013 Elsevier B.V.


Anderson D.P.,Landcare Research | Ramsey D.S.L.,Arthur Rylah Institute for Environmental Research | Nugent G.,Landcare Research | Bosson M.,Animal Health Board | And 5 more authors.
Epidemiology and Infection | Year: 2013

Surveying and declaring disease freedom in wildlife is difficult because information on population size and spatial distribution is often inadequate. We describe and demonstrate a novel spatial model of wildlife disease-surveillance data for predicting the probability of freedom of bovine tuberculosis (caused by Mycobacterium bovis) in New Zealand, in which the introduced brushtail possum (Trichosurus vulpecula) is the primary wildlife reservoir. Using parameters governing home-range size, probability of capture, probability of infection and spatial relative risks of infection we employed survey data on reservoir hosts and spillover sentinels to make inference on the probability of eradication. Our analysis revealed high sensitivity of model predictions to parameter values, which demonstrated important differences in the information contained in survey data of host-reservoir and spillover-sentinel species. The modelling can increase cost efficiency by reducing the likelihood of prematurely declaring success due to insufficient control, and avoiding unnecessary costs due to excessive control and monitoring. Copyright © Cambridge University Press 2013.


Moore S.J.,Murdoch University | O'Dea M.A.,Western Australian Department of Agriculture and Food | Perkins N.,AusVet Animal Health Services | O'Hara A.J.,Murdoch University
Journal of Veterinary Diagnostic Investigation | Year: 2015

The prevalence of organisms known to be associated with bovine respiratory disease (BRD) was investigated in cattle prior to export. A quantitative reverse transcription polymerase chain reaction assay was used to detect nucleic acids from the following viruses and bacteria in nasal swab samples: Bovine coronavirus (BoCV; Betacoronavirus 1), Bovine herpesvirus 1 (BoHV-1), Bovine viral diarrhea virus 1 (BVDV-1), Bovine respiratory syncytial virus (BRSV), Bovine parainfluenza virus 3 (BPIV-3), Histophilus somni, Mycoplasma bovis, Mannheimia haemolytica, and Pasteurella multocida. Between 2010 and 2012, nasal swabs were collected from 1,484 apparently healthy cattle destined for export to the Middle East and Russian Federation. In addition, whole blood samples from 334 animals were tested for antibodies to BoHV-1, BRSV, BVDV-1, and BPIV-3 using enzyme-linked immunosorbent assay. The nasal prevalence of BoCV at the individual animal level was 40.1%. The nasal and seroprevalence of BoHV-1, BRSV, BVDV-1, and BPIV-3 was 1.0% and 39%, 1.2% and 46%, 3.0% and 56%, and 1.4% and 87%, respectively. The nasal prevalence of H. somni, M. bovis, M. haemolytica, and P. multocida was 42%, 4.8%, 13.4%, and 26%, respectively. Significant differences in nasal and seroprevalence were detected between groups of animals from different geographical locations. The results of the current study provide baseline data on the prevalence of organisms associated with BRD in Australian live export cattle in the preassembly period. This data could be used to develop strategies for BRD prevention and control prior to loading. © 2014 The Author(s).


Madin B.,Murdoch University | Madin B.,AusVet Animal Health Services
Preventive Veterinary Medicine | Year: 2011

Foot and Mouth Disease (FMD) is considered to be endemic throughout mainland South-East Asia (SEA). The South-East Asia and China FMD (SEACFMD) campaign is a regional control programme which has been ongoing since 1997. The programme encourages countries to submit reports of outbreaks regularly. This paper evolved from a collaboration with SEACFMD to evaluate 10 years worth of reporting. All publicly available outbreak reports (5237) were extracted from the ASEAN Region Animal Health Information System (ARAHIS) for the period from 2000 to mid 2010. These reports included date, outbreak location (at the province and district level) and serotype (if known) plus information on the outbreak size and affected species. Not all records had complete information on the population at-risk or the number of animals affected. This data was transferred into a spatially enabled database (along with data from other sources) and analysed using R and SaTScan. Outbreak serotype was unknown in 2264 (43%) of reports and some countries had very few laboratory confirmed cases (range <1-86%). Outbreak reports were standardised by number of villages in each province. Outbreak intensity varied however there did not appear to be a consistent pattern, nor was there any seasonal trend in outbreaks. Spatial and spatio-temporal cluster detection methods were applied. These identified significant clusters of disease reports. FMD is endemic across the region but is not uniformly present. ARAHIS reports can be regarded as indicators of disease reporting: there may be reports in which laboratory confirmation has not occurred, and in some cases clinical signs are inconsistent with FMD. This raises questions about the specificity of the data. Advances in decentralised testing techniques offer hope for improved verification of FMD as the cause of disease outbreaks. Advances in molecular typing may provide a substantial leap forward in understanding the circulation of FMD in South East Asia. © 2011 Elsevier B.V.


Gordon R.,AusVet Animal Health Services | Bresolin-Schott N.,Plant Health Australia | East I.J.,GPO Box 858
Australian Veterinary Journal | Year: 2014

Objective: To examine the nomadic movements of Australian beekeepers and determine their potential to assist the spread of pests and diseases. Methods: A questionnaire was mailed to all beekeepers in Australia who maintained >100 hives, requesting information on the location of their home base, locations used throughout the year and the crops that the bees fed on in each location. The information was analysed using network analysis software and a geographic information system. Results: Nomadic Australian beekeepers formed a connected network linking 288 locations from central Queensland to western Victoria. A second, smaller network included 42 locations in south-eastern South Australia. Almond orchards in Robinvale and Boundary Bend and lucerne seed production in Keith were locations of major hive congregations driven by the opportunity to provide paid pollination services. In the 3months after completion of almond pollination in August 2008, movement of hives occurred from Robinvale and Boundary Bend to 49 locations, ranging from south-east Queensland to south-west Victoria. Discussion: The movements identified in this study highlight the potential for rapid spread of disease or pests throughout the beekeeping industry should an incursion occur. © 2014 Australian Veterinary Association.


East I.J.,Khan Research Laboratories | Davis J.,Khan Research Laboratories | Sergeant E.S.G.,AusVet Animal Health Services | Garner M.G.,Khan Research Laboratories
Australian Veterinary Journal | Year: 2014

Objective: To assess management practices and movement patterns that could influence the establishment and spread of exotic animal diseases (EAD) in pigs in Australia. Methods: A literature review of published information and a telephone survey of 370 pig producers owning >10 pigs who were registered with the PigPass national vendor declaration scheme. Results: The movement and marketing patterns of Australian pig producers interviewed were divided into two groups based predominantly on the size of the herd. Major pig producers maintain closed herds, use artificial insemination and market direct to abattoirs. Smaller producers continue to purchase from saleyards and market to other farms, abattoirs and through saleyards in an apparently opportunistic fashion. The role of saleyards in the Australian pig industry continues to decline, with 92% of all pigs marketed directly from farm to abattoir. Conclusions: This survey described movement patterns that will assist in modelling the potential spread of EAD in the Australian pig industry. Continued movement towards vertical integration and closed herds in the Australian pig industry effectively divides the industry into a number of compartments that mitigate against the widespread dissemination of disease to farms adopting these practices. © 2014 Australian Veterinary Association.


Morgan K.,University of Liverpool | Cameron A.,AusVet Animal Health Services | Gustafson L.,U.S. Department of Agriculture
Journal of Applied Aquaculture | Year: 2015

This aim of this article is to enable the reader to implement a surveillance system. System is defined as “a set of interacting and interdependent components that have a function, i.e., inputs and outputs” and surveillance as “the ongoing systematic collection and analysis of data and the provision of information that leads to action being taken to prevent and control disease.” It includes practical exercises as well as theoretical information to assist in getting surveillance from the computer to the farm. It recognizes that management theory and information technology are as important as epidemiology in implementing surveillance. Copyright © Taylor & Francis Group, LLC.


Bischofberger A.S.,University of Sydney | Dart C.M.,University of Sydney | Perkins N.R.,Ausvet Animal Health Services | Dart A.J.,University of Sydney
Veterinary Surgery | Year: 2011

Objective: To determine the effect of manuka honey on second-intention healing of contaminated, full-thickness skin wounds in horses. Study Design: Experimental. Animals: Adult Standardbred horses (n = 8). Methods: One wound was created on the dorsomedial aspect of the third metacarpus in both forelimbs, contaminated with feces, and bandaged for 24 hours. Bandages were removed and wounds rinsed with isotonic saline solution. Wounds on 1 limb had manuka honey applied daily (n = 8) whereas wounds on the contralateral limb received no treatment (n = 8). Bandages were replaced and changed daily for 12 days, after which treatment stopped, bandages were removed, leaving wounds open to heal. Wound area was measured 24 hours after wound creation (day 1), then weekly for 8 weeks. Overall time for healing was recorded. Wound area and rate of healing of treated and control wounds were compared statistically. Results: Treatment with manuka honey decreased wound retraction and treated wounds remained significantly smaller than control wounds until day 42; however, there was no difference in overall healing time between treatment and control wounds. Conclusions: Treatment with manuka honey reduced wound area by reducing retraction but did not affect overall healing time of full-thickness distal limb wounds using this wound-healing model. ©2011 by The American College of Veterinary Surgeons.


Cameron A.R.,AusVet Animal Health Services
Preventive Veterinary Medicine | Year: 2012

Output-based surveillance standards provide a mechanism to achieve harmonised and comparable surveillance (which meets a defined objective) while allowing flexible approaches that are adapted to the different populations under surveillance. When correctly implemented, they can result in lower cost and greater protection against disease spread. This paper presents examples of how risk-based sampling can improve the efficiency of surveillance, and describes the evolution of output-based surveillance standards for demonstration of freedom from disease in terms of three generations of approach: surveillance sensitivity, probability of freedom, and expected cost of error.These three approaches progressively capture more of the factors affecting the final outcome. The first two are relatively well accepted but the third is new and relates to the consequences of infection.There has been an increased recognition of the value of risk-based sampling for demonstration of freedom from disease over the last decades, but there has been some disagreement about practical definitions and implementation, in particular as to whether 'risk-based' implies probability of infection or probability and consequences. This paper argues that risk-based sampling should be based solely on the probability of infection of a unit within the population, while the consequences of infection should be used to set the target probability of freedom. This approach provides a quantitative framework for planning surveillance which is intuitively understandable. The best way to find disease, if it is present, is to focus on those units that are most likely to be infected. However, if the purpose of surveillance includes mitigating the risk of a disease outbreak, we want to ensure that that risk is smallest in those populations where the consequences of failure to detect are greatest. © 2012 Elsevier B.V.


Moore S.J.,Murdoch University | O'Dea M.A.,WA | Perkins N.,AusVet Animal Health Services | Barnes A.,Murdoch University | O'Hara A.J.,Murdoch University
Journal of Veterinary Diagnostic Investigation | Year: 2014

The cause of death in 215 cattle on 20 long-haul live export voyages from Australia to the Middle East, Russia, and China was investigated between 2010 and 2012 using gross, histologic, and/or molecular pathology techniques. A quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay was used to detect nucleic acids from viruses and bacteria known to be associated with respiratory disease in cattle: Bovine coronavirus (Betacoronavirus 1), Bovine herpesvirus 1, Bovine viral diarrhea virus 1 and 2, Bovine respiratory syncytial virus, Bovine parainfluenza virus 3, Histophilus somni, Mycoplasma bovis, Mannheimia haemolytica, and Pasteurella multocida. The most commonly diagnosed cause of death was respiratory disease (107/180, 59.4%), followed by lameness (n = 22, 12.2%), ketosis (n = 12, 6.7%), septicemia (n = 11, 6.1%), and enteric disease (n = 10, 5.6%). Two thirds (130/195) of animals from which lung samples were collected had histologic changes and/or positive qRT-PCR results indicative of infectious lung disease: 93 out of 130 (72%) had evidence of bacterial infection, 4 (3%) had viral infection, and 29 (22%) had mixed bacterial and viral infections, and for 4 (3%) the causative organism could not be identified. Bovine coronavirus was detected in up to 13% of cattle tested, and this finding is likely to have important implications for the management and treatment of respiratory disease in live export cattle. Results from the current study indicate that although overall mortality during live export voyages is low, further research into risk factors for developing respiratory disease is required. © 2014 The Author(s).

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