Positive association between Brucella spp seroprevalences in livestock and humans from a cross-sectional study in Garissa and Tana River Counties, Kenya
Authors: Kairu-Wanyoike S.W. , Nyamwaya D. , Wainaina M. , Lindahl J. , Ontiri E. , Bukachi S. , Njeru I. , Karanja J. , sang R. , Grace D. , Bett B. 
Published: June 2019

Background

Brucella spp. is a zoonotic bacterial agent of high public health and socio-economic importance. It infects many species of animals including wildlife, and people may get exposed through direct contact with an infected animal or consumption of raw or undercooked animal products. We implemented a linked livestock-human cross-sectional study to determine seroprevalences and risk factors of Brucella spp. in livestock and humans. We also estimated intra-cluster correlation coefficients (ICCs) for these observations at the household and village levels.

Methodology

The study was implemented in Garissa County (specifically Ijara and Sangailu areas) and Tana River (Bura and Hola) counties. A household was the unit of analysis and the sample size was derived using the standard procedures. Serum samples were obtained from selected livestock and people from randomly selected households. Humans were sampled in both counties while livestock could be sampled only in Tana River County. Samples obtained were screened for anti-Brucella IgG antibodies using ELISA kits. Data were analyzed using generalized linear mixed effects logistic regression models with the household (herd) and village being used as random effects.

Results

The overall seroprevalences were 3.47% (95% confidence interval [CI]: 2.72 – 4.36%) and 35.81% (95% CI: 32.87 – 38.84) in livestock and humans, respectively. In livestock, older animals and those sampled in Hola had significantly higher seroprevalences that younger ones or those sampled in Bura. Herd and village random effects were significant and ICC estimates associated with these variables were 0.40 (95% CI: 0.22 – 0.60) and 0.24 (95% CI: 0.08 – 0.52), respectively. For human data, older people, males, and people who lived in pastoral areas had significantly higher Brucella spp. seroprevalences than younger ones, females or those who lived in irrigated or riverine areas. People from households that had at least one seropositive animal were 3.35 (95% CI: 1.51 – 7.41) times more likely to be seropositive compared to those that did not. Human exposures significantly clustered at the household level; the ICC estimate obtained was 0.21 (95% CI: 0.06 – 0.52).

Conclusion

The presence of a seropositive animal in a household significantly increased the risk of exposure in people in that household. Brucella spp. exposures in both livestock and humans clustered significantly at the household level. This suggests that risk-based surveillance measures, guided by locations of primary cases reported, either in humans or livestock, can be used to detect Brucella spp. infections livestock or humans, respectively.

Author summary

Brucellosis is an important zoonotic disease that primarily affects livestock and wildlife. In humans, the disease is characterized by prolonged fever, body aches, joint pains and weakness while in livestock, the disease causes abortions and infertility. We carried out a study in northeastern Kenya (Garissa and Tana River Counties) to identify factors that affect the distribution of the disease in people and livestock. Livestock and people from randomly selected households were recruited and serum samples obtained for screening using anti-Brucella IgG ELISA kits to determine their Brucella spp. exposure. Data obtained were analyzed using mixed effects logistic regression models. Results obtained show that human and animal Brucella spp. seroprevalences cluster at the household level. The odds of exposure in humans were at least three times higher in households that had at least one seropositive animal compared to those that did not. These results can be used to design risk-based surveillance systems where each Brucella infection identified in livestock or humans could signal potential locations of other secondary infections.