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Beasley EM, Nelson KM, Slate D, Gilbert AT, Pogmore FE, Chipman RB, Davis AJ. Oral Rabies Vaccination of Raccoons (Procyon lotor) across a Development Intensity Gradient in Burlington, Vermont, USA, 2015-2017. J Wildl Dis 2024; 60:1-13. [PMID: 37972639 DOI: 10.7589/jwd-d-22-00117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 06/27/2022] [Indexed: 11/19/2023]
Abstract
Management of the raccoon rabies virus variant in North America is conducted primarily using oral rabies vaccination (ORV). When a sufficient proportion of the population is vaccinated (∼60%), rabies transmission can be eliminated. To date, ORV programs have successfully controlled and eliminated raccoon rabies in rural areas, but there has been less success in urban areas. We studied the proportions of rabies virus neutralizing antibodies (RVNA) in a raccoon (Procyon lotor) population during a 3-yr ORV trial in developed areas of Burlington, Vermont, US. We used a modified N-mixture model to estimate raccoon abundance, RVNA seroprevalence, and capture rates jointly to examine factors that relate to ORV success to better inform management. We found that raccoon abundance was lower in less-developed areas compared to urban centers. Raccoon RVNA seroprevalence decreased as population abundance increased; it increased as the average age of the population increased. Nontarget opossum (Didelphis virginiana) captures correlated with a decrease in raccoon RVNA seroprevalence in low-development areas, suggesting that they may be competing for baits. The target bait density across the entire study area was 150 baits/km2, but a hand baiting strategy was heavily concentrated on roads, resulting in uneven bait densities within sampling sites (0-484 baits/km2). Uneven bait distribution across the study area may explain low RVNA seroprevalence in some locations. Our results suggest that increases in bait density across the study area may improve RVNA seroprevalence and support annual ORV to account for raccoon population turnover.
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Affiliation(s)
- Emily M Beasley
- University of Vermont, Department of Biology, 109 Carrigan Drive, Burlington, Vermont 05401, USA
- Current affiliation: Université de Montréal, Département de Sciences Biologiques, 1375 Avenue Thérèse-Lavoie-Roux, Montréal, Quebec H2V 0B3, Canada
- These authors contributed equally
| | - Kathleen M Nelson
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Rabies Management Program, 59 Chenell Drive, Suite 2, Concord, New Hampshire 03301, USA
- These authors contributed equally
| | - Dennis Slate
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Rabies Management Program, 59 Chenell Drive, Suite 2, Concord, New Hampshire 03301, USA
- Current affiliation: Chippewa Bay Wildlife Art and Science LLC, 1132 County Road 6, Hammond, New York 13646, USA
| | - Amy T Gilbert
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, Colorado 80521, USA
| | - Frederick E Pogmore
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, 617 Comstock Road, Suite 9, Berlin, Vermont 05602, USA
| | - Richard B Chipman
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Rabies Management Program, 59 Chenell Drive, Suite 2, Concord, New Hampshire 03301, USA
| | - Amy J Davis
- United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, National Wildlife Research Center, 4101 Laporte Avenue, Fort Collins, Colorado 80521, USA
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Cardia Caserta L, Mansano do Nascimento G, Joshi LR, Mausbach Simão R, Miller ME, Nunes Felippe PA, Diel DG, Weis Arns C. Bacterial and Viral Diversity of Didelphid Opossums from Brazil. Ecohealth 2023; 20:362-369. [PMID: 38091183 DOI: 10.1007/s10393-023-01667-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 11/28/2023] [Indexed: 02/21/2024]
Abstract
Marsupials belonging to the Didelphis genus are widely distributed in the American Continent, and Didelphis albiventris and Didelphis aurita, are common in all of their areas of distribution in Brazil. Here we describe the bacterial and viral diversity of samples from opossums captured in three forest fragments in the State of São Paulo, Brazil. Microbiomes from the same body site were more similar across species and sampling sites while oral swabs presented higher bacterial diversity than rectal swabs. We also identified sequences related to bacterial species involved in zoonotic diseases. The detection of pathogens in such abundant mammal species warns for the possibility of emergence in other species.
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Affiliation(s)
- Leonardo Cardia Caserta
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas - UNICAMP, Campinas, Brazil.
- Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, 240 Farrier Road, Ithaca, NY, 14853, USA.
| | - Gabriela Mansano do Nascimento
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas - UNICAMP, Campinas, Brazil
- Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, 240 Farrier Road, Ithaca, NY, 14853, USA
| | - Lok Raj Joshi
- Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, 240 Farrier Road, Ithaca, NY, 14853, USA
| | - Raphael Mausbach Simão
- Programa de Pós-Graduação em Epidemiologia Experimental Aplicada às Zoonoses, Faculdade de Medicina Veterinária e Zootecnia (FMVZ-USP), São Paulo, Brazil
| | - Michael E Miller
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas - UNICAMP, Campinas, Brazil
| | - Paulo A Nunes Felippe
- Departamento de Proteção e Bem-Estar Animal - Prefeitura de Campinas, Campinas, SP, Brazil
| | - Diego G Diel
- Department of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, 240 Farrier Road, Ithaca, NY, 14853, USA
| | - Clarice Weis Arns
- Departamento de Genética, Evolução, Microbiologia e Imunologia, Instituto de Biologia, Universidade Estadual de Campinas - UNICAMP, Campinas, Brazil
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Bigler LL, Ochwat JB, Scarpitta SC, Matthews BW, Rudd RJ, Lein DH. ORAL RABIES VACCINATION STRATEGIES TOWARD RACCOON (PROCYON LOTOR) RABIES ELIMINATION ON SUBURBAN LONG ISLAND, NEW YORK, USA. J Wildl Dis 2021; 57:132-44. [PMID: 33635968 DOI: 10.7589/2018-02-033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 05/17/2018] [Indexed: 11/20/2022]
Abstract
Approximately 1.86 million baits containing a vaccinia-rabies glycoprotein recombinant vaccine were distributed with helicopters, vehicles, and bait stations during 2006-10. A bait density of 250 baits/km2 effectively controlled rabies cases in enzootic and preepizootic areas. However, a cluster of 11 rabid raccoons at the eastern edge of infection resulted in the initiation of semiannual, high-density (500 baits/km2) vaccination campaigns in approximately 20% of the oral rabies vaccination zone during July and September (2007-09). Bait success (i.e., chewed sachets or removed baits) at bait stations was negatively associated with station distances from water. Conversely, bait success improved with increasing distances from roads. Bait stations deployed significantly more baits in developed open space when compared to low- and medium- to high-intensity developed areas. However, a difference was not detected between developed open space and forest habitats. Rabies was confined to 86 raccoons within 317 km2 (10%) of a 3,133 km2 suburban landscape, with a disproportionate number of rabid raccoons (n=74) in developed areas, when compared to 10 cases in forest-wetland habitats. Two rabid raccoons did not fall within either general land-use classification. Rabies advanced 15.1 km eastward at a rate of 6.4 km/yr during a 28-mo interval (2004-06).
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Chen R, Little R, Mihaylova L, Delahay R, Cox R. Wildlife surveillance using deep learning methods. Ecol Evol 2019; 9:9453-9466. [PMID: 31534668 PMCID: PMC6745675 DOI: 10.1002/ece3.5410] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 05/20/2019] [Accepted: 05/23/2019] [Indexed: 11/26/2022] Open
Abstract
Wildlife conservation and the management of human-wildlife conflicts require cost-effective methods of monitoring wild animal behavior. Still and video camera surveillance can generate enormous quantities of data, which is laborious and expensive to screen for the species of interest. In the present study, we describe a state-of-the-art, deep learning approach for automatically identifying and isolating species-specific activity from still images and video data.We used a dataset consisting of 8,368 images of wild and domestic animals in farm buildings, and we developed an approach firstly to distinguish badgers from other species (binary classification) and secondly to distinguish each of six animal species (multiclassification). We focused on binary classification of badgers first because such a tool would be relevant to efforts to manage Mycobacterium bovis (the cause of bovine tuberculosis) transmission between badgers and cattle.We used two deep learning frameworks for automatic image recognition. They achieved high accuracies, in the order of 98.05% for binary classification and 90.32% for multiclassification. Based on the deep learning framework, a detection process was also developed for identifying animals of interest in video footage, which to our knowledge is the first application for this purpose.The algorithms developed here have wide applications in wildlife monitoring where large quantities of visual data require screening for certain species.
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Affiliation(s)
- Ruilong Chen
- Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
| | - Ruth Little
- Department of GeographyUniversity of SheffieldSheffieldUK
| | - Lyudmila Mihaylova
- Department of Automatic Control and Systems EngineeringUniversity of SheffieldSheffieldUK
| | - Richard Delahay
- National Wildlife Management CentreAnimal and Plant Health AgencyGloucestershireUK
| | - Ruth Cox
- National Wildlife Management CentreAnimal and Plant Health AgencyGloucestershireUK
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Rupprecht CE, Dietzschold B. Special Issue: Rabies Symptoms, Diagnosis, Prophylaxis, and Treatment. Trop Med Infect Dis 2017; 2:E59. [PMID: 30270916 PMCID: PMC6082069 DOI: 10.3390/tropicalmed2040059] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Accepted: 11/08/2017] [Indexed: 11/17/2022] Open
Abstract
Rabies is an acute, progressive, incurable viral encephalitis found throughout the world. Despite being one of the oldest recognized pathogens, its impact remains substantial in public health, veterinary medicine, and conservation biology.[...].
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Affiliation(s)
| | - Bernhard Dietzschold
- Department of Microbiology and Immunology, Thomas Jefferson University, Philadelphia, PA 19107, USA.
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