Mapping eastern equine encephalitis virus risk for white-tailed deer in Michigan |
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| Institution: | 1. School of Geosciences, University of South Florida, 4202 E. Fowler Ave., Tampa, FL 33620, USA;2. Washington State Department of Health, Olympia, WA 98504, USA;3. College of Public Health, University of South Florida, 4202 E. Fowler Ave., Tampa, FL 33620, USA;1. Department of Thoracic and Cardiovascular Surgery, Uijeongbu St. Mary''s Hospital, The Catholic University of Korea College of Medicine, Seoul, Korea;2. Department of Thoracic and Cardiovascular Surgery, St. Paul''s Hospital, The Catholic University of Korea College of Medicine, Seoul, Korea;1. Section of Ecology, Department of Biology, University of Turku, Turku, Finland;2. School of Biological Sciences, Monash University, Victoria, Australia;1. School of Veterinary Science, Massey University, Palmerston North, New Zealand;2. Gribbles Veterinary Pathology Ltd., Christchurch, New Zealand;3. Vetlife Oxford, Oxford, New Zealand |
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| Abstract: | Eastern equine encephalitis (EEE) is a mosquito-borne viral disease that is often fatal to humans and horses. Some species including white-tailed deer and passerine birds can survive infection with the EEE virus (EEEV) and develop antibodies that can be detected using laboratory techniques. In this way, collected serum samples from free ranging white-tailed deer can be used to monitor the presence of the virus in ecosystems. This study developed and tested a risk index model designed to predict EEEV activity in white-tailed deer in a three-county area of Michigan. The model evaluates EEEV risk on a continuous scale from 0.0 (no measurable risk) to 1.0 (highest possible risk). High risk habitats are identified as those preferred by white-tailed deer that are also located in close proximity to an abundance of wetlands and lowland forests, which support disease vectors and hosts. The model was developed based on relevant literature and was tested with known locations of infected deer that showed neurological symptoms. The risk index model accurately predicted the known locations, with the mean value for those sites equal to the 94th percentile of values in the study area. The risk map produced by the model could be used refine future EEEV monitoring efforts that use serum samples from free-ranging white-tailed deer to monitor viral activity. Alternatively, it could be used focus educational efforts targeted toward deer hunters that may have elevated risks of infection. |
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| Keywords: | Arbovirus Disease mapping GIS Wildlife |
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