BMC Veterinary Research 2015, Vol. 11:189Background: Brucellosis is a zoonosis of public health importance worldwide. In Tanzania, the disease is underreported due to insufficient awareness, inadequate diagnostic protocols, including lack of appropriate reagents for diagnosis. Livestock and wildlife are considered potential sources of infection to humans; however, the role played by these carriers in the epidemiology of the disease in the ecosystems in Tanzania is not fully understood. The objective of this study was to establish the prevalence of anti-Brucella antibodies in humans, wildlife and livestock; and molecular prevalence of Brucella spp in cattle and goats in the Katavi- Rukwa ecosystem. Results: Anti-Brucella antibodies were detected in humans at 0.6 % (95 % CI: 0.1, 2.1 %); cattle at 6.8 % (95 % CI: 5.4, 8.5 %), goats at 1.6 % (95 % CI: 0.4, 4.1 %) and buffaloes at 7.9 % (95 % CI: 1.7, 21.4 %). One of the two sampled lions tested positive. Cattle had a significantly higher prevalence of anti-Brucella antibodies as compared to goats (P < 0.05). A significantly higher seroprevalence was found in female than in male cattle and in adult than in young cattle (P < 0.05). There was an agreement of 95 and 89 % in cattle and goats, respectively, for the Rose Bengal plate Test (RBPT) and Competitive Enzyme Linked Immunosorbent Assay (c-ELISA) in detecting Brucella infection. Eight (3.5 %) out of 231 milk samples tested were positive for Brucella spp on Polymerase Chain Reaction (PCR), and Brucella abortus biovar 1 was detected in cattle milk. However, no Brucella spp were detected in goat milk. Conclusion: This study has shown the presence of anti- Brucella antibodies in humans, livestock, and wildlife in the Katavi- Rukwa ecosystem. Transmission of the infection between wildlife, livestock and humans is likely to continue due to increasing human activities in the human wildlife interface. This information is an important contribution to public health policy development in the human wildlife interface of the Katavi- Rukwa ecosystem.