Epidemiology of Theileria bicornis among black and white rhinoceros metapopulation in Kenya

BACKGROUND: A huge effort in rhinoceros conservation has focused on poaching and habitat loss as factors leading to the dramatic declines in the endangered eastern black rhinoceros (Diceros bicornis michaeli) and the southern white rhinoceros (Ceratotherium simum simum). Nevertheless, the role disease and parasite infections play in the mortality of protected populations has largely received limited attention. Infections with piroplasmosis caused by Babesia bicornis and Theileria bicornis has been shown to be fatal especially in small and isolated populations in Tanzania and South Africa. However, the occurrence and epidemiology of these parasites in Kenyan rhinoceros is not known. RESULTS: Utilizing 18S rRNA gene as genetic marker to detect rhinoceros infection with Babesia and Theileria, we examined blood samples collected from seven rhinoceros populations consisting of 114 individuals of black and white rhinoceros. The goal was to determine the prevalence in Kenyan populations, and to assess the association of Babesia and Theileria infection with host species, age, sex, location, season and population mix (only black rhinoceros comparing to black and white rhinoceros populations). We did not detect any infection with Babesia in the sequenced samples, while the prevalence of T. bicornis in the Kenyan rhinoceros population was 49.12% (56/114). White rhinoceros had significantly higher prevalence of infection (66%) compared to black rhinoceros (43%). The infection of rhinoceros with Theileria was not associated with animal age, sex or location. The risk of infection with Theileria was not higher in mixed species populations compared to populations of pure black rhinoceros. CONCLUSION: In the rhinoceros studied, we did not detect the presence of Babesia bicornis, while Theileria bicornis was found to have a 49.12% prevalence with white rhinoceros showing a higher prevalence (66%) comparing with black rhinoceros (43%). Other factors such as age, sex, location, and population mix were not found to play a significant role.