Author : Paul Christopher Ramey
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (639 download)
Book Synopsis Population Density and Prevalence of Rabies Virus-neutralizing Antibodies in a Northern Ohio Raccoon Population by : Paul Christopher Ramey
Download or read book Population Density and Prevalence of Rabies Virus-neutralizing Antibodies in a Northern Ohio Raccoon Population written by Paul Christopher Ramey and published by . This book was released on 2005 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current oral rabies vaccination (ORV) programs across the eastern USA were established to prevent the westward spread of raccoon (Procyon lotor) rabies. The programs distribute vaccine baits at a density of 75 baits/km2. However, few studies have examined the relationship of bait density and population density to sero-prevalence of rabies virus-neutralizing antibodies (RVNA). I conducted experimental baitings in August 2003 and 2004, 150 km west of the ORV zone (Sandusky, Ohio) where there was no history of raccoon rabies. I collected blood samples from live-trapped raccoons to determine sero-prevalence of RVNA, and teeth to determine prevalence of tetracycline (biomarker in bait). During April-October (2003 and 2004), I evaluated 3 mark-recapture-based estimates of raccoon population density, as well as a line-transect-based method on the 22-km2 U.S. National Aeronautics and Space Administration Plum Brook Station in Erie County, Ohio (USA; 41° 27' N, 82° 42' W). During 2003, 41% of pre-bait serum samples were RVNA positive (>̲ 0.05 IU/ml), but none had titers>̲ 0.25 IU/ml. During the pre-2004 bait drop period (March-August) 21% of samples collected were RVNA positive and 9% had titers>̲ 0.25 lU/ml. After the 2003 and 2004 bait drops (September-October) only 4% of serum samples collected had high titers. Prevalence of tetracycline in post-bait teeth indicated that 17% and 27% of the population ingested baits in 2003 and 2004, respectively. I first calculated annual minimum number known alive (MNKA) density estimates, approximating the protocol used by the U.S. Department of Agriculture Wildlife Services, and estimated an adult population size of 660 raccoons and 594 raccoons during 2003 and 2004, respectively. I also estimated size of the adult population using the catch per unit effort (CPUE) method, which yielded 438 ± 182 raccoons and 527 ± 208 raccoons for 2003 and 2004 respectively. Using program CAPTURE and model Mbh (heterogeneity and trap response), I estimated a population size of 619 ± 83 during 2003 and 765 ± 92 during 2004. Using Distance (version 4.1) and the line-transect data, I estimated 198 raccoons and 220 raccoons for 2003 and 2004, respectively. During 2003 and 2004 both, surveys resulted in density estimates less than the number of unique individuals captured. I note that lack of replication in the MNKA model precludes error estimates. Also, assumptions of equal probability of capture for both the MNKA and CPUE estimates were violated, likely biasing my estimates low. However, the upper limit of the CPUE estimate in both years was similar to mean estimates from the mark-recapture model. I suggest that mark-recapture would serve well in providing density information in ORV planning. Further, in situations where trapping would be difficult due to trap exposures (e.g., urban settings), estimates based on line-transect data from FLIR could provide a baseline to estimate the target population density. I attribute the low proportions of high RVNA titers and tetracycline to the high density of raccoons on the study area. I estimated an adult population of 619 ± 83 (95% CI) raccoons, using 2003 data and model Mbh. Assuming an annual birthrate of 1.5 juveniles per adult, 1,548 raccoons were present at the time of the 2003 baiting, so just under 1 bait was distributed per raccoon, well below the program target of 5 baits/raccoon. A high proportion of RVNA positive raccoons in an area with no history of raccoon rabies or vaccination efforts exemplifies the need for pre-bait serology in order to accurately measure the effect of ORV distribution. I contend that without incorporating pre-bait serology and population density estimates, an ORV program could under-bait high-density populations and overestimate the number of vaccinated animals.
