Issuing Body

Mississippi State University

Advisor

Burger, L. Wes, Jr.

Committee Member

Leopold, Bruce D.

Committee Member

Vilella, Francisco J.

Committee Member

Jack, Sherman W.

Committee Member

Huston, Carla L.

Other Advisors or Committee Members

Cranfield, Michael R.

Date of Degree

1-1-2006

Document Type

Dissertation - Open Access

Abstract

The Mountain Gorillas of Central Africa are one of the most highly endangered species in the world, with only 740 individuals surviving. One of the greatest threats to this species is disease. Health of wildlife is continually garnering more attention in the public arena due to recent outbreaks of diseases such as West Nile and High Pathogenic Avian Influenza. However, no system currently exists to facilitate the management and analysis of wildlife health data. The research conducted herein was the development and testing of a health information monitoring system for the mountain gorillas entitled Internet-supported Management Program to Assist Conservation Technologies or IMPACT?. The system functions around a species database of known or unknown individuals and provides individual-based and population-based epidemiological analysis. The system also uses spatial locations of individuals or samples to link multiple species together based on spatial proximity for inter-species comparisons. A syndromic surveillance system or clinical decision tree was developed to collect standardized data to better understand the ecology of diseases within the gorilla population. The system is hierarchical in nature, using trackers and guides to conduct daily observations while specially trained veterinarians are used to confirm and assess any abnormalities detected. Assessment of the decision tree indicated that trackers and guides did not observe gorilla groups or individuals within groups similarly. Data suggests that, to be consistent, trackers and guides need to conduct observations even on the day that veterinarians collect data. Validity and reliability remain to be tested in the observation instrument. Assessment of pathogen loads and distributions within species surrounding the gorillas indicates that humans have the greatest pathogen loads with 13 species, followed by cattle and chimpanzees (11), baboon (10), gorillas (9), and rodents (3). Spatial aggregation occurred in Cryptosporidium, Giardia, and Trichuris; however, there is reason to question the test results of the former 2 species. These data suggest that researchers need to examine the impact of local human and domestic animal populations on gorillas and other wildlife.

URI

https://hdl.handle.net/11668/19110

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