Application of Geographic Information Systems to Identify African Great Ape Populations at Greater Risk from Human Diseases
Jonathan M. Sleeman, MA, VetMB, DACZM, MRCVS
Wildlife Center of Virginia, Waynesboro, VA, USA; Virginia Department of Game and Inland Fisheries, Richmond, VA, USA
Recent outbreaks of zoonotic diseases in African great apes illustrate the potential role of infectious diseases in jeopardizing the persistence of great ape populations. The objective of this unique study was to illustrate the potential application of Geographic Information Systems (GIS) to generate hypotheses regarding which African great ape populations, including bonobos (Pan paniscus), chimpanzees (Pan troglodytes), and gorillas (Gorilla gorilla and Gorilla beringei), are at increased risk from human diseases. The most recently available (2000) human demographic data and core human health indicator data for the African great ape range countries were obtained from the Centers for Disease Control and Prevention and World Health Organization websites. Human population density and percent annual human population growth rate were used as combined indicators of environmental stress/vulnerability (as a proxy measure of human-great ape contact), and infant mortality rate (IMR) and healthy life expectancy (HALE) were used as separate indicators of disease burden among the human populations living in the great ape range countries. Cutoff values were determined, and using GIS (SIGEpi, Pan American Health Organization, Washington, DC), these indicators were analyzed to create maps of critical areas (countries) with both environmental stress and high burden of human diseases. When using IMR as the indicator of disease burden, the great ape range countries identified as critical areas included Benin, Guinea-Bissau, Ivory Coast, Liberia, Nigeria and Tanzania. Cameroon and Uganda were also identified as critical areas when using HALE as the indicator of disease burden; however, Benin was excluded. Including geospatially referenced maps of great ape populations in the analysis would then identify at-risk populations within these critical areas. Validation of the results would allow for targeted interventions such as increased disease surveillance of at-risk great apes, improved public health in the critical areas, as well as educational programs regarding zoonoses, thereby maximizing the use of limited resources. Further analyses should be performed at the first and second administrative boundary levels to identify within-country critical areas for human–great ape disease transmission. Improvements in public health infrastructure in these critical areas would benefit the human populations that have unmet health needs as well as these endangered species. This illustrates the connectivity between human and wildlife health and provides a conservation-related argument for improvement of public health in these developing countries.