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Investigation into disease events at the wildlife/livestock interface: lessons learned from bovine viral diarrhea virus in Colorado cervids

dc.contributor.authorDuncan, Colleen, author
dc.contributor.authorSalman, Mo, advisor
dc.contributor.authorVanCampen, Hana, advisor
dc.date.accessioned2024-03-13T19:26:13Z
dc.date.available2024-03-13T19:26:13Z
dc.date.issued2009
dc.description.abstractInfectious agents may be transmitted between wild and domestic animals; these so called 'interface diseases' can have significant economic consequences. As such, effective tools and techniques with which to study disease in free ranging, wild animals is essential. Principles of wildlife disease surveillance were reviewed and it was concluded that while wildlife disease research may require unique logistical adaptations; basic principles of surveillance remain the same. A review of wildlife data sources utilized for surveillance suggests that information collected, and shared, is dependent on the group involved and that there are opportunities to improve the type and quality of material available. Bovine viral diarrhea virus (BVDV) is an important virus of domestic cattle that has recently been identified in wild ruminants worldwide. To investigate the presence, prevalence, distribution and significance of BVDV in wild cervids of Colorado a series of projects were conducted. Persistently infected (PI) deer were studied post mortem; immunohistochemical and molecular techniques used to look for viral antigen in deer tissue were found to be effective supporting the use of these tests in further studies. The prevalence and distribution of PI cervids in the state was evaluated using an opportunistic sampling technique; the prevalence is extremely low, but naturally occurring infection is present within Colorado. The cost associated with testing animals for an uncommon disease may be very high; techniques like pooling samples can help to keep costs down during such investigations. The sensitivity and specificity of RT-PCR on pooled samples was investigated in an experimental study and revealed that supernatant from a single positive deer skin sample may be diluted up to 10,000 times and still be detected. Another technique to focus research efforts on high risk areas is the use of simulation modeling. A stochastic risk assessment model was developed to identify regions in Colorado where PI cattle were likely to be born following exposure to a PI deer. Results of the model were consistent with both the cross-sectional survey for PI cervids and other reports on BVDV in wildlife of Colorado.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierETDF_Duncan_2009_3374642.pdf
dc.identifier.urihttps://hdl.handle.net/10217/237698
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.licensePer the terms of a contractual agreement, all use of this item is limited to the non-commercial use of Colorado State University and its authorized users.
dc.subjectbovine viral diarrhea virus
dc.subjectcervids
dc.subjectdisease surveillance
dc.subjectlivestock
dc.subjectpersistent infection
dc.subjectwildlife disease
dc.subjectanimal sciences
dc.subjectforestry
dc.subjectanimal diseases
dc.titleInvestigation into disease events at the wildlife/livestock interface: lessons learned from bovine viral diarrhea virus in Colorado cervids
dc.typeText
dcterms.rights.dplaThis Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
thesis.degree.disciplineClinical Sciences
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)

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