Positive association between Brucella spp. seroprevalences in livestock and humans from a cross-sectional study in Garissa and Tana River Counties, Kenya

PLoS Negl Trop Dis. 2019 Oct 17;13(10):e0007506. doi: 10.1371/journal.pntd.0007506. eCollection 2019 Oct.

Abstract

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. A linked livestock-human cross-sectional study to determine seroprevalences and risk factors of brucellosis in livestock and humans was designed. Estimates were made for intra-cluster correlation coefficients (ICCs) for these observations at the household and village levels.

Methodology: The study was implemented in Garissa (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 Brucella spp. 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 than 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. In humans, Brucella spp. seroprevalence was significantly higher in older people, males, and people who lived in pastoral areas 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 Brucella spp.-seropositive animal in a household significantly increased the odds of Brucella spp. seropositivity in humans in that household. Exposure to Brucella spp. of 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 in livestock or humans, respectively.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Animals
  • Antibodies, Bacterial / blood
  • Brucella
  • Brucellosis / epidemiology*
  • Brucellosis / immunology*
  • Brucellosis / microbiology
  • Brucellosis / veterinary*
  • Cross-Sectional Studies
  • Female
  • Humans
  • Immunoglobulin G / blood
  • Kenya / epidemiology
  • Livestock / microbiology*
  • Logistic Models
  • Male
  • Risk Factors
  • Rivers
  • Seroepidemiologic Studies*
  • Surveys and Questionnaires
  • Young Adult
  • Zoonoses / epidemiology
  • Zoonoses / microbiology

Substances

  • Antibodies, Bacterial
  • Immunoglobulin G

Grants and funding

This study was part of the project: Dynamic Drivers of Disease in Africa: Ecosystems, livestock/wildlife, health and wellbeing NE-J001570-1 that was jointly funded by the Ecosystem Services for Poverty Alleviation, Programme (ESPA). The ESPA programme is funded by the Department for International Development (DFID), the Economic and Social Research Council (ESRC) and the Natural Environment Research Council (NERC). Other funding was provided by the CGIAR Research Program Agriculture for Nutrition and Health (A4NH) led by IFPRI. The contribution of JL was supported by the Swedish Research Council. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.