RESUMO
BACKGROUND: Zoonoses account for most of the emerging and re-emerging infections in Kenya and in other low to medium-income countries across the world. The human-livestock-wildlife interface provides a nexus where transmission and spread of these zoonotic diseases could occur among communities farming in these areas. We sought to identify perceptions of the community living near the Lake Nakuru National Park in Kenya. METHODS: We used participatory epidemiology techniques (PE) involving Focus Group Discussion (FGD) among community members and Key Informant Interviews (KII) with the health, veterinary, and administration officers in July 2020. We used listing, pairwise matching, and proportional piling techniques during the FGDs in the randomly selected villages in the study area from a list of villages provided by the area government officers. Kruskal-Wallis test was used to compare the median scores between the zoonotic diseases, source of information, and response to disease occurrence. Medians with a z-score greater than 1.96 at 95% Confidence Level were considered to be significant. Content analysis was used to rank qualitative variables. RESULTS: We conducted seven FGDs and four KIIs. A total of 89 participants took part in the FGDs with their ages ranging from 26 to 85 years. Common zoonotic diseases identified by participants included anthrax, rabies, and brucellosis. Anthrax was considered to have the greatest impact by the participants (median = 4, z>1.96), while 4/7 (57%) of the FGDs identified consumption of uninspected meat as a way that people can get infected with zoonotic diseases. Community Health Volunteers (Median = 28, z = 2.13) and the government veterinary officer (median = 7, z = 1.8) were the preferred sources of information during disease outbreaks. CONCLUSION: The participants knew the zoonotic diseases common in the area and how the diseases can be acquired. We recommend increased involvement of the community in epidemio-surveillance of zoonotic diseases at the human-wildlife-livestock interface.
